Miracle-dz/UniFAR-FTUs huggingface dataset:
Bolometric temperature and young stars in the Taurus and Ophiuchus complexes

We calculated bolometric temperature (T(sub bol)) and luminosity (L(sub bol)) for 128 young stellar objects (YSOs) in Taurus, 74 in the Ophiuchus 'core', and 33 in the Ophiuchus 'off-core' region. We have constructed the bolometric luminosity-temperature (BLT) diagram, the log-log plot of L(sub bol) versus T(sub bol), for the three samples. T(sub bol) is defined as the temperature of a blackbody having the same frequency as the observed continuum spectrum. It measures the redness (or coldness) of an astronomical source. The BLT diagram is analogous to the H-R diagram and allows for a direct and quantitative comparison of YSOs at a wide variety of evolutionary states, ranging from the most deeply embedded stars to T Tauri stars nearly on the main sequence. We found (1) T(sub bol) increases monotonically from embedded sources (approximately 60-500 K) to classical T Tauri stars (approximately 1000-3000 K) to weak-line T Tauri stars (approximately 2000-5000 K); (2) T(sub bol) correlates reasonably well with the age inferred from the evolutionary models of pre-main-sequence stars and protostars for embedded 'protostars' and weak-line T Tauri stars. There is no significant correlation for the classical T Tauri stars. These results can be understood in terms of dissipation of circumstellar dust envelope and disk during the early stages of stellar evolution. Sources in the three regions have different distributions in the BLT diagram. The Ophiuchus core has the highest fraction of cold sources among the three regions. These cold sources are also more luminous than the YSOs in the other regions. The Ophiuchus off-core sample is dominated by the more evolved pre-main-sequence stars. The Taurus sources have distributions intermediate in L(sub bol), T(sub bol), and age between the Ophiuchus core and off-core distributions. These may suggest differences in the star formation history, and possibly in the stellar masses and mass accretion rates in these star-forming regions.
On the Convergence of the Density of Terras' Set

The Collatz Conjecture's connection to dynamical systems opens it to a variety of techniques aimed at recurrence and density results. First, we turn to density results and strengthen the result of Terras through finding a strict rate of convergence. This rate gives a preliminary result on the Triangle Conjecture, which describes a set nodes that would dominate $L^{C} = \{y \in \N \, | \, T^{k}(y)>y , \,\forall k \in \N \}$. Second, we extend prior arguments to show that the construction of several classes of measures imply the bounded trajectories piece of the Collatz Conjecture.
Improved Prediction of Turbomachinery Flows Using Near-Wall Reynolds-Stress Model

In this paper an assessment of the improvement in the prediction of complex turbomachinery flows using a new near-wall Reynolds-stress model is attempted. The turbulence closure used is a near-wall low-turbulence-Reynolds-number Reynolds-stress model, that is independent of the distance-from-the-wall and of the normal-to-the-wall direction. The model takes into account the Coriolis redistribution effect on the Reynolds-stresses. The five mean flow equations and the seven turbulence model equations are solved using an implicit coupled O(Δx 3 ) upwind-biased solver. Results are compared with experimental data for three turbomachinery configurations: the NTUA high subsonic annular cascade, the NASA―37 rotor, and the RWTH 1 1/2 stage turbine. A detailed analysis of the flowfield is given. It is seen that the new model that takes into account the Reynolds-stress anisotropy substantially improves the agreement with experimental data, particularily for flows with large separation, while being only 30 percent more expensive than the k-e model (thanks to an efficient implicit implementation). It is believed that further work on advanced turbulence models will substantially enhance the predictive capability of complex turbulent flows in turbomachinery.
Local isotropy and large structures in a heated turbulent jet

Recent measurements of the skewness of the derivative of the temperature fluctuation θ, implying the breakdown of local isotropy even in high Reynolds number shear flows, are examined. Using the temperature signal in a slightly heated axisymmetric jet, a detailed quantitative analysis is made of the suggestion that the observed presence of a well-defined large-scale pattern of the temperature signal in these flows is responsible for this breakdown. A selective ensemble averaging technique is used for separating this pattern from fluctuations superposed on it. The technique is extended to extract the large-scale patterns in simultaneously measured axial (u), radial (v) velocity fluctuations, and the products uv, uθ and vθ, so that it is possible to separate contributions of these patterns from those of the superposed fluctuations to several important turbulent quantities. The mean shape of the patterns, their degree of anisotropy and correlation, and their contribution to turbulence intensities and Reynolds shear stress are obtained. Probability densities and spectra of these quasi-homogeneous superposed fluctuations are also obtained. Results show that the fluctuations are consistent with local isotropy and make the dominant contribution to the turbulence intensities, that the large-scale patterns are responsible for the observed skewness values of the derivative of v, and that the fluctuations may be responsible for a significant part of the turbulent momentum and heat transport, especially in the region of the jet where the turbulent energy production is substantial.
Drop Size Distributions for Irrigation Spray Nozzles

DROP size distributions for irrigation spray nozzles, such as may be used in low or reduced pressure sprinkler systems, were measured with a calibrated stain technique. Similar data from other sources, measured with photographic or pellet techniques, were also obtained. The distributions were fitted with the upper limit log normal (ULLN) distribution function. ULLN parameters for each distribution are tabulated. Distribution characteristics such as the volume median drop size may be calculated directly from the ULLN parameters. A simple regression model for predicting ULLN parameters as functions of nozzle style, size and pressure is proposed and fitted to data for flooding and smooth flat plate spray nozzles. The fit of model to data was evaluated by comparing measured and predicted values for 50th (median) and 99th (volume) percentile drop sizes, and by directly comparing measured and predicted distribution functions. The distance between functions was defined analogous to the Euclidean distance between points in space, leading to definition of a pseudo r2 for the (functional) regression model. The fit between data and model for the two nozzle types was quite good. The models were used to explore the influence of nozzle size and pressure on drop size distributions for the two types of nozzles.
Monitoring of variations in the speed of sound in contracting and relaxing muscle

Beside of changes in the shape of contracting and relaxing muscle, which can be monitored with ultrasound, also changes in the velocity of ultrasound are expected. To observe such changes with high resolution for the gastrocnemius muscle of athletes a novel detection scheme has been developed. As already introduced for the detection of sideways expansion of the muscle, ultrasonic transducers are mounted sideways on opposing positions of the skin. To detect variations of the speed of sound, the expansion of the muscle is suppressed by mechanical clamping. Under this condition, any variation in the time-of-flight of ultrasonic signals can only be introduced by a variation of the speed of sound along the path of the ultrasound transit signal. The observed rather small variations of the speed of sound are compared to the signals obtained by ultrasound monitoring for the extension and contraction observed for free sideways motion (unclamped muscle). Opposite to the general behavior of a free muscle the clamped muscle shows a diminishing time-of-flight under contraction relating to an increase in the sound velocity. Since clamping also reduces effects of inertia, the influence of inertia on muscle dynamics can be illustrated by comparison of measurements on clamped and free muscle.
Probability, Random Processes, and Estimation Theory for Engineers

1. (Note: Each chapter concludes with Problems and References)2. Introduction to Probability3. Random Variables4. Functions of Random Variables5. Averages6. Vector Random Variables7. Estimation and Decision Theory I8. Random Sequences9. Random Processes10. Mean-Square Calculus11. Stationary Processes and Sequences12. Estimation Theory II13. Appendix: Review of Relevant Mathematics14. Index15. Information for Using the Program Disk
Global output tracking for nonlinear systems

The well-known local results on output tracking makes it possible to control the state so that the output follows some desired path $y_d$ over some time interval $[t_0 ,t_0 + \varepsilon )$. These results have been extended to give global tracking, so that the output follows $y_d$ over a given interval $[t_0 ,t_1 ]$, for a class of systems that are sufficiently “observable. ” An example is presented to illustrate how these results can be used to steer the state of the system from a given initial state to a desired final state.
Gender-based social norms, psychosocial variation, and power relations during delivery and postnatal care: a case study qualitative research in rural Ethiopia

Background: Background: The World Health Organization (WHO) strongly encourages men to support women in using maternal healthcare services. However, especially in developing countries, maternal health care has traditionally been viewed as a women's issue, with men making little or no contribution, despite the fact that sexuality and children are shared products. The study's goal was to understand how gender-based norms, psychosocial variation, power relations, and community social support are related to child delivery and post-natal care services. Method: The study took place in three rural districts of Ethiopia's Oromia regional state, Jimma Zone. An in-depth interview and focus group discussion were held with a group of carefully chosen health professionals, community health development armies, and religious leaders. The data was collected, translated, and transcribed by men and women with experience in qualitative research. For data analysis, Atlas ti version 9 was used. Gender-based delivery and postnatal care service utilization were investigated using gender-based categories. Result: Independent and shared gender-based roles were identified as a means to improve maternal healthcare services delivery. Men have the ability to persuade pregnant women to use delivery services and post-natal care. The place of delivery is determined by the levels of gender power relations at the household level, but women are usually the final decision-makers. Furthermore, the community's belief that giving birth in a health facility makes women look clean and neat, as opposed to home delivery, increases their intention to use maternal health care services. Conclusion: Understanding men's and women's roles, knowledge levels, beliefs, decision-making, and social support significantly improves maternal healthcare service utilization, allowing pregnant women to receive delivery services at a health facility. Pregnant women were the last to make a decision about using maternal health care services. There are still gaps in knowledge and negative beliefs about maternal health care that limit delivery and postnatal service utilization. Recommendation: Increasing community-level social support can significantly improve maternal healthcare service delivery. Men's concern about institutional delivery is increased when they are viewed as the primary audience during maternal health education. Researchers should focus on the mechanisms through which men participate in delivery in the future, and postnatal services will fully address men's involvement in maternal health care services.
Integrated microbiome and metabolome analysis reveals the interaction between intestinal flora and serum metabolites as potential biomarkers in hepatocellular carcinoma patients

Globally, liver cancer poses a serious threat to human health and quality of life. Despite numerous studies on the microbial composition of the gut in hepatocellular carcinoma (HCC), little is known about the interactions of the gut microbiota and metabolites and their role in HCC. This study examined the composition of the gut microbiota and serum metabolic profiles in 68 patients with HCC, 33 patients with liver cirrhosis (LC), and 34 healthy individuals (NC) using a combination of metagenome sequencing and liquid chromatography−mass spectrometry (LC−MS). The composition of the serum metabolites and the structure of the intestinal microbiota were found to be significantly altered in HCC patients compared to non-HCC patients. LEfSe and metabolic pathway enrichment analysis were used to identify two key species (Odoribacter splanchnicus and Ruminococcus bicirculans) and five key metabolites (ouabain, taurochenodeoxycholic acid, glycochenodeoxycholate, theophylline, and xanthine) associated with HCC, which then were combined to create panels for HCC diagnosis. The study discovered that the diagnostic performance of the metabolome was superior to that of the microbiome, and a panel comprised of key species and key metabolites outperformed alpha-fetoprotein (AFP) in terms of diagnostic value. Spearman’s rank correlation test was used to determine the relationship between the intestinal flora and serum metabolites and their impact on hepatocarcinogenesis and progression. A random forest model was used to assess the diagnostic performance of the different histologies alone and in combination. In summary, this study describes the characteristics of HCC patients’ intestinal flora and serum metabolism, demonstrates that HCC is caused by the interaction of intestinal flora and serum metabolites, and suggests that two key species and five key metabolites may be potential markers for the diagnosis of HCC.
Robust variable selection for the varying coefficient model based on composite L 1–L 2 regression

The varying coefficient model (VCM) is an important generalization of the linear regression model and many existing estimation procedures for VCM were built on L 2 loss, which is popular for its mathematical beauty but is not robust to non-normal errors and outliers. In this paper, we address the problem of both robustness and efficiency of estimation and variable selection procedure based on the convex combined loss of L 1 and L 2 instead of only quadratic loss for VCM. By using local linear modeling method, the asymptotic normality of estimation is driven and a useful selection method is proposed for the weight of composite L 1 and L 2. Then the variable selection procedure is given by combining local kernel smoothing with adaptive group LASSO. With appropriate selection of tuning parameters by Bayesian information criterion (BIC) the theoretical properties of the new procedure, including consistency in variable selection and the oracle property in estimation, are established. The finite sample performance of the new method is investigated through simulation studies and the analysis of body fat data. Numerical studies show that the new method is better than or at least as well as the least square-based method in terms of both robustness and efficiency for variable selection.
Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation

Continual learning entails learning a sequence of tasks and balancing their knowledge appropriately. With limited access to old training samples, much of the current work in deep neural networks has focused on overcoming catastrophic forgetting of old tasks in gradient-based optimization. However, the normalization layers provide an exception, as they are updated interdependently by the gradient and statistics of currently observed training samples, which require specialized strategies to mitigate recency bias. In this work, we focus on the most popular Batch Normalization (BN) and provide an in-depth theoretical analysis of its sub-optimality in continual learning. Our analysis demonstrates the dilemma between balance and adaptation of BN statistics for incremental tasks, which potentially affects training stability and generalization. Targeting on these particular challenges, we propose Adaptive Balance of BN (AdaB$^2$N), which incorporates appropriately a Bayesian-based strategy to adapt task-wise contributions and a modified momentum to balance BN statistics, corresponding to the training and testing stages. By implementing BN in a continual learning fashion, our approach achieves significant performance gains across a wide range of benchmarks, particularly for the challenging yet realistic online scenarios (e.g., up to 7.68%, 6.86% and 4.26% on Split CIFAR-10, Split CIFAR-100 and Split Mini-ImageNet, respectively). Our code is available at https://github.com/lvyilin/AdaB2N.
Binge Eating in a Slovenian Population-based Sample of Adults

Abstract Introduction Binge eating is the most common form of disordered eating associated with obesity, reduced quality of life, and medical and psychological comorbidities. It therefore affects the well-being of individuals. This underscores the fact that it is a serious public health problem. The study aimed to investigate binge eating and anxiety across gender, age and body mass index in a large population sample of adults in Slovenia. Methods A total of 3,310 adult volunteers participated in this cross-sectional study. Questionnaires, including a binge eating and anxiety scale and an eating behaviour questionnaire, were completed by 1,487 subjects (90.9% female, ages 18 to 69). Results The frequency of reported binge eating was 29.9%, with 9.8% of participants reporting severe binge eating, and the presence of overweight and obesity was high (41.8%). BMI was associated with this problematic eating, and explained 5.4% of the variation in binge eating. Importantly, anxiety was the most important factor related to binge eating, with younger participants and women reporting significantly more anxiety. Conclusion The high presence of binge eating, obesity and anxiety in the Slovenian population-based sample is worrying. Anxiety is clearly an important factor in understanding the relationship between negative affect and binge eating, as it accounts for a greater proportion of the variance in binge eating symptoms than BMI. Particularly concerning was the fact that the youngest participants showed the greatest anxiety. Targeting anxious adolescents and females is important from a health perspective because it can impact the physical and mental health of the population in the long term.
Optical and near-infrared simultaneous observations of the BL Lacs PKS 2005-489 and PKS 2155-304

Aims. In this work, we looked for simultaneous brigthness variations in the optical and near-infrared bands in the TeV BL Lacs PKS 2005-489 and PKS 2155-304, covering time scales from minutes to a few years. Methods. Between 2001 and 2003, we carried out optical and near-infrared observations using two telescopes at the Pico dos Dias Observatory (LNA, Brazil), reaching a time resolution in the light curves of about 14 min at optical wavelengths and 6 min in the infrared. For both sources the variability analysis was done after the contribution of the host galaxy was subtracted from the observed flux. Results. In PKS 2005-489 we detected for the first time optical and near-infrared variations on time scales of minutes. Both sources presented variability on different time scales and with complex and distinct spectral behavior. This behavior favors a scenario in which the variability is produced by the formation and fast evolution of shock waves in the quiescent or slowly varying nuclear jet.
Nonvanishing of L-series associated to cubic twists of elliptic curves

has a rational solution. An extensive compilation of the older history of the problem is given in Dickson [6]. Within the past century, researchers have tried to exploit (either explicitly or unknowingly) the fact that the curve (0.1) is in fact an elliptic curve. During the nineteenth century, Lucas, and later Sylvester, used a descent argument to prove that (0.1) had no solution for infinitely many D in certain congruence classes mod 9 and 18 (see [6], Ch. XXI). Zagier and Kramarz [19] have produced a great deal of numerical evidence about the L-series of the curves; based on these computations, they have argued heuristically that for
Public perceptions of digital fashion: An analysis of sentiment and Latent Dirichlet Allocation topic modeling

Since digital technology has had a significant impact on the fashion industry, digital fashion has become a hot topic in today’s society. Currently, research on digital fashion is focused on the transformation of enterprise marketing strategies and the discussion of digital technology. Despite this, the current study does not include an analysis of the audience’s emotional and cognitive responses to digital fashion on social networking platforms. A comprehensive analysis and discussion of 52,891 posts about digital fashion and virtual fashion published on social networking sites was conducted using k-means clustering analysis, Latent Dirichlet Allocation (LDA) topic modeling, and sentiment analysis in this study. The study examines the public’s perception and hot topics about digital fashion, as well as the industry’s development situation and trends. According to the findings, both positive and neutral emotions accompany the public’s attitude toward digital fashion. There is a wide range of topics covered in the discussion. Innovations in digital technology have impacted the creation of jobs, talent demand, marketing strategies, profit forms, and industrial chain innovation of fashion-related businesses. Researchers in related fields will find this study useful not only as a reference for research methods and directions, but also as a source of references for research methodology. A case study and data reference will also be provided to industry practitioners.
Editorial: Regenerative surgery of the cornea

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On the Eigenfunction Expansions Associated with Fredholm Integral Equations of First Kind in the Presence of Noise

In this paper we consider the eigenfunction expansions associated with Fredholm integral equations of first kind when the data are perturbed by noise. We prove that these expansions are asymptotically convergent, in the sense of L 2 -norm, when the bound of the noise tends to zero. This result allows us to construct a continuous mapping from the data space to the solution space, without using any constraint or a priori bound. We can also show a probabilistic version of this result, which is based on the order)disorder transition in the Fourier coefficients of the noisy data. From these results one can derive algorithms and in particular statisti- cal methods able to furnish approximations of the solution without any use of prior knowledge. Q 1996 Academic Press, Inc.