Miracle-dz/UniFAR-FTUs huggingface dataset:
Marriage Pattern and Fertility in DKI Jakarta Province

Birth rate or fertility is one of the elements playing a role in determining the population number and age structure in an area. To maintain stable population growth, it is necessary to strive for a total fertility rate (TFR) of around 2.1 children per woman. DKI Jakarta Province had reached this condition before the 2000 period. But in the next period, there was an increase ranging from 2.2 - 2.3 children per woman. Fertility is affected by various factors, including marriage patterns and contraception usage. This study aims to determine the effect of marriage patterns on fertility in DKI Jakarta Province by using the concept of fertility decomposition. The data used are the results of the Indonesian Demographic and Health Survey (IDHS) 2002/03 and 2017 with the unit of analysis for women aged 15-49 years. The results showed that there was a slight increase in the effect of the marriage pattern on fertility restrictions, from 14% or preventing 1.89 births in the 2002/03 IDHS to 19% or preventing the occurrence of 2.1 births in the 2017 IDHS. in DKI Jakarta Province by 2.2 children per woman in the 2017 IDHS, although there was a sharp decline in the effect of contraceptive use. It is necessary to study the relationship between the pattern of marriage and the use of contraception because these two variables play an important role in determining the fertility rate in DKI Jakarta Province.
Detection of H I 21 Centimeter Absorption by the Warm Neutral Medium

We have detected H I 21 cm line absorption by the warm neutral medium (WNM) using the Westerbork synthesis radio telescope. The absorption was detected toward Cygnus A at LSR velocities of -40 and -70 km s−1. These two velocity ranges were previously identified as being relatively free of cold absorbing clouds. The measured optical depth for the WNM along the line of sight to Cygnus A is (8.9 ± 1.9) × 10−4 at -70 km s−1 and (8.5 ± 2.0) × 10−4 at -40 km s−1, with corresponding spin temperatures of 6000 ± 1700 and 4800 ± 1600 K, respectively. The volume filling factor for the WNM appears to be fairly high (f ≈ 0.4).
The Association between Spicy Food Consumption and Psychological Health in Chinese College Students: A Cross-Sectional Study

Background: Capsaicin is the main active ingredient in chili peppers and spicy food. Animal studies provide contradictory results on the role of capsaicin in psychiatric disorders. There are no epidemiological studies to investigate the relationship between spicy food consumption and psychological health. Methods: A cross-sectional online survey was conducted. Psychological health was assessed with the Depression Anxiety Stress Scale, and spicy food consumption was assessed as frequency, strength, and duration of consumption. Multivariable logistic regression was conducted to determine the associations between spicy food consumption and psychological symptoms. Results: Our sample comprised 1771 participants (male = 674, mean age = 21.97 years). The odds of having depressive, anxiety, and stress symptoms were 34.0%, 46.5%, and 19.1% in Chinese college students, respectively. After adjusting for a series of covariates, compared with non-consumers, the odds ratios (ORs) of depressive symptoms across spicy food consumption were 1.13 (95% CI: 0.87–1.46) for 1–2 days/week and 1.38 (95% CI: 1.02–1.86) for ≥3 days/week. With regard to anxiety symptoms, the ORs were 0.99 (95% CI: 0.78, 1.27) for 1–2 days/week and 1.50 (95% CI: 1.13–1.99) for ≥3 days/week. For stress symptoms, the ORs were 0.90 (95% CI: 0.66–1.23) for 1–2 days/week and 1.27 (95% CI: 0.89–1.80) for ≥3 days/week. The ORs for the depressive symptoms associated with different intensities of spicy food consumption were 1.00 (reference) for the reference group (non-consumers), 1.17 (95% CI: 0.90–1.52) for eating weakly spicy food, and 1.34 (95% CI: 1.01–1.78) for moderately to strongly spicy food. Conclusion: The findings suggested a positive association between frequently spicy food consumption and depressive/anxiety symptoms in adolescents, and no such association was found for stress symptoms.
Most general flat space boundary conditions in three-dimensional Einstein gravity

We consider the most general asymptotically flat boundary conditions in three-dimensional Einstein gravity in the sense that we allow for the maximal number of independent free functions in the metric, leading to six towers of boundary charges and six associated chemical potentials. We find as associated asymptotic symmetry algebra an isl(2)k current algebra. Restricting the charges and chemical potentials in various ways recovers previous cases, such as bms3, Heisenberg or Detournay–Riegler, all of which can be obtained as contractions of corresponding AdS3 constructions. Finally, we show that a flat space contraction can induce an additional Carrollian contraction. As examples we provide two novel sets of boundary conditions for Carroll gravity.
Galaxy shape measurement with convolutional neural networks

We present our results from training and evaluating a convolutional neural network (CNN) to predict galaxy shapes from wide-field survey images of the first data release of the Dark Energy Survey (DES DR1). We use conventional shape measurements as ‘ground truth’ from an overlapping, deeper survey with less sky coverage, the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS). We demonstrate that CNN predictions from single band DES images reproduce the results of CFHTLenS at bright magnitudes and show higher correlation with CFHTLenS at fainter magnitudes than maximum likelihood model fitting estimates in the DES Y1 im3shape catalogue. Prediction of shape parameters with a CNN is also extremely fast, it takes only 0.2 ms per galaxy, improving more than 4 orders of magnitudes over forward model fitting. The CNN can also accurately predict shapes when using multiple images of the same galaxy, even in different colour bands, with no additional computational overhead. The CNN is again more precise for faint objects, and the advantage of the CNN is more pronounced for blue galaxies than red ones when compared to the DES Y1 metacalibration catalogue, which fits a single Gaussian profile using riz band images. We demonstrate that CNN shape predictions within the metacalibration self-calibrating framework yield shear estimates with negligible multiplicative bias, m < 10−3, and no significant point spread function (PSF) leakage. Our proposed set-up is applicable to current and next-generation weak lensing surveys where higher quality ‘ground truth’ shapes can be measured in dedicated deep fields.
Efficient Graph-Based Energy Minimization Methods in Computer Vision

Energy minimization is an elegant approach to computer vision. Vision problems usually have many solutions due to uncertainties in the imaging process and ambiguities in visual interpretation. The energy function encodes the problem constraints, and its minimum gives the optimal solution. Despite numerous advantages, this approach is severely limited by the high computational cost. The main contribution of my thesis lies in developing efficient combinatorial optimization algorithms for several important classes of energy functions which incorporate everywhere smooth, piecewise constant, and piecewise smooth priors. These priors assume, respectively, that the quantity to be estimated varies smoothly over its domain, consist of several pieces with constant values, or consist of several pieces with smoothly varying values. The algorithms rely on graph cuts as a powerful optimization technique. For a certain everywhere smooth prior we develop an algorithm which finds the exact minimum by computing a single graph cut. This method is most suitable to estimate quantities without discontinuities. But even when discontinuities exist, the method produces good results in certain cases. The running time is low order polynomial. For several wide classes of piecewise smooth priors we develop two approximation algorithms (we show that exact minimization in NP-hard in these cases). These algorithms produce a local minimum in interesting large move spaces. Furthermore, one of them finds a solution within a known factor from the optimum. The algorithms are iterative and compute several graph cuts at each iteration. The running time at each iteration is effectively linear due to the special graph structure. In practice it takes just a few iterations to converge. Moreover most of the progress happens during the first iteration. For a certain piecewise constant prior we adapt the algorithms developed for the piecewise smooth prior. One of them finds a solution within a factor of two from the optimum. In addition we develop a third algorithm which finds a local minimum in yet another move space. We demonstrate the effectiveness of our approach on image restoration, stereo, and motion. For the data with ground truth, our methods significantly outperform standard methods.
Analysis of the Ecosystem Characteristics and Ecological Carrying Capacity of the Main Commercial Fish in the Artificial Reef Ecosystem in Laizhou Bay Using the Ecopath Model

In this study, we constructed an Ecopath model of the artificial reef ecosystem in Laizhou Bay, with special emphasis on the stock enhancement opportunities. Laizhou Bay is the largest semi-enclosed bay in the Bohai Sea, China, where multiple factors, especially overfishing, have led to the decline of many commercial marine fish stocks. Artificial oyster reefs were developed in 2011 in this region, providing shelter, feeding, and breeding sites for marine organisms. Additionally, stock enhancement by release can be used to replenish fishery species resources. Ad hoc stock enhancement, however, can fail to bring economic benefits and may impact ecosystem stability. Therefore, we estimated the ecological carrying capacity of the three main economic fish species in Laizhou Bay, including black rockfish (Sebastes schlegelii), fat greening (Hexagrammos otakii), and Chinese seabass (Lateolabrax maculatus) before release to ensure the sustainable use of fishery resources. The Ecopath model in Laizhou Bay was divided into 17 functional groups based on commercial relevance, dietary similarity, and habitat needs of the species present in the area. The ecological parameters, such as the ratio of total primary productivity to total respiration (1.205), connectance index (0.207), and system omnivory index (0.090) indicated that the artificial reef ecosystem in Laizhou Bay has a relatively simple food web structure. The ecological carrying capacities of S. schlegelii, H. otakii, and L. maculatus were assessed at 0.4676 t/km2, 0.5472 t/km2, and 0.3275 t/km2, respectively. This study provides a reference for the formulation of fishery strategies to maintain ecosystem stability and biodiversity and to maximize fishery returns and sustainability in Laizhou Bay.
A Fast and Accurate Method to Capture the Solar Corona/Transition Region Enthalpy Exchange

The brightness of the emission from coronal loops in the solar atmosphere is strongly dependent on the temperature and density of the confined plasma. After a release of energy, these loops undergo a heating and upflow phase, followed by a cooling and downflow cycle. Throughout, there are significant variations in the properties of the coronal plasma. In particular, the increased coronal temperature leads to an excess downward heat flux that the transition region (TR) is unable to radiate. This generates an enthalpy flux from the TR to the corona, increasing the coronal density. The enthalpy exchange is highly sensitive to the TR resolution in numerical simulations. With a numerically underresolved TR, major errors occur in simulating the coronal density evolution and, thus, the predicted loop emission. This Letter presents a new method that addresses the difficulty of obtaining the correct interaction between the corona and corona/chromosphere interface. In the TR, an adaptive thermal conduction approach is used that broadens any unresolved parts of the atmosphere. We show that this approach, referred to as TRAC, successfully removes the influence of numerical resolution on the coronal density response to heating while maintaining high levels of agreement with fully resolved models. When employed with coarse spatial resolutions, typically achieved in multidimensional MHD codes, the peak density errors are less than 3% and the computation time is three orders of magnitude faster than fully resolved field-aligned models. The advantages of using TRAC in field-aligned hydrodynamic and multidimensional magnetohydrodynamic simulations are discussed.
Flexible Prior Models: Three‐dimensional ionospheric tomography

A three‐dimensional ionospheric reconstruction system is presented that models ionospheric dynamics and accounts for well‐known limitations in the available data by using geometrically transformed prior models based on available models, such as the Parameterized Ionospheric Model (PIM) or the International Reference Ionosphere (IRI), to produce density solutions consistent with available Total Electron Content (TEC) measurement data. It is known that current state of the art prior density models, such as PIM or IRI, can only simulate a statistical mean ionosphere. As a result, sudden variations in ionospheric electron density will not be represented in these models. This paper focuses on a three‐dimensional ionospheric density reconstruction system that uses a set of geometrical transformations to produce Flexible Prior Models (FPM). The Flexible Prior Model process allows means to include flexibility in a prior model in the form of geometrical variations that are not well represented in current state‐of‐the‐art ionospheric prior density models. The updated priors are used as initial solution models for a set of (A, B) Multiplicative Algebraic Reconstruction Technique (ABMART) algorithms, that can easily incorporate additional information and provide a spatially constrained density solution, consistent with the available data and our current knowledge of ionospheric dynamics. The ultimate goal is to create a three‐dimensional adaptive ionospheric electron density reconstruction system that would make it possible to generate real‐time ionospheric maps supported by available TEC data. Such maps would be of significant utility in predicting and correcting the impact of electron density gradients and irregularities on radio waves.
Long-term English learners’ mathematics course trajectories: downstream consequences of early remediation on college preparation

ABSTRACT We investigated how high school mathematics course placement contributes to inequalities in college preparation for students categorized as “English Learners” (ELs), especially “long-term” English Learners (LTELs). We devised a base-2 enumeration approach that allowed us to process complex transcript data from one school district and enumerate the thousands of possible trajectories (combinations) of mathematics courses taken by students during high school. We observed significant disparities in college preparation across students by English proficiency designation. In comparison to English Only (EO) students, LTELs were funneled into fewer trajectories that predominantly included lower level mathematics courses. We found that enrollment into remedial mathematics courses in Grade 9 appears to restrict access to advanced courses, with grave consequences for Grade 12 college preparation.
The Pharmacorank Search Tool for the Retrieval of Prioritized Protein Drug Targets and Drug Repositioning Candidates According to Selected Diseases

We present the Pharmacorank search tool as an objective means to obtain prioritized protein drug targets and their associated medications according to user-selected diseases. This tool could be used to obtain prioritized protein targets for the creation of novel medications or to predict novel indications for medications that already exist. To prioritize the proteins associated with each disease, a gene similarity profiling method based on protein functions is implemented. The priority scores of the proteins are found to correlate well with the likelihoods that the associated medications are clinically relevant in the disease’s treatment. When the protein priority scores are plotted against the percentage of protein targets that are known to bind medications currently indicated to treat the disease, which we termed the pertinency score, a strong correlation was observed. The correlation coefficient was found to be 0.9978 when using a weighted second-order polynomial fit. As the highly predictive fit was made using a broad range of diseases, we were able to identify a general threshold for the pertinency score as a starting point for considering drug repositioning candidates. Several repositioning candidates are described for proteins that have high predicated pertinency scores, and these provide illustrative examples of the applications of the tool. We also describe focused reviews of repositioning candidates for Alzheimer’s disease. Via the tool’s URL, https://protein.som. geisinger.edu/Pharmacorank/, an open online interface is provided for interactive use; and there is a site for programmatic access.
Immunomodulatory Effects of Chicken Broth and Histidine Dipeptides on the Cyclophosphamide-Induced Immunosuppression Mouse Model

The carnosine and anserine, which represent histidine dipeptides (HD), are abundant in chicken broth (CB). HD are endogenous dipeptide that has excellent antioxidant and immunomodulatory effects. The immunomodulatory effect of CB hydrolysate (CBH) and HD in cyclophosphamide (CTX)-induced immunosuppressed mice was examined in this study. CBH and HD were given to mice via oral gavage for 15 days, accompanied by intraperitoneal CTX administration to induce immunosuppression. CBH and HD treatment were observed to reduce immune organ atrophy (p < 0.05) and stimulate the proliferation of splenic lymphocytes (p < 0.05) while improving white blood cell, immunoglobulin M (IgM), IgG, and IgA levels (p < 0.05). Moreover, CBH and HD strongly stimulated interleukin-2 (IL-2) and interferon-gamma (IFN-γ) production by up-regulating IL-2 and IFN-γ mRNA expression (p < 0.05) while inhibiting interleukin-10 (IL-10) overproduction and IL-10 mRNA expression (p < 0.05). In addition, CBH and HD prevented the inhibition of the nitric oxide (NP)/cyclic guanosine monophosphate-cyclic adenosine monophosphate (cGMP-cAMP)/protein kinase A (PKA) signaling pathway (p < 0.05). These results indicate that CBH and HD have the potential to prevent immunosuppression induced by CTX. Our data demonstrate that CBH can effectively improve the immune capacity of immunosuppressed mice similar to the same amount of purified HD, which indicates that CBH plays its role through its own HD.
Star formation history of Canis Major OB1 II. A bimodal X-ray population revealed by XMM-Newton

The Canis Major OB1 Association has an intriguing scenario of star formation, especially in the Canis Major R1 (CMa R1) region traditionally assigned to a reflection nebula, but in reality an ionized region. This work is focused on the young stellar population associated to CMa R1, for which our previous results from ROSAT, optical and near-infrared data had revealed two stellar groups with different ages, suggesting a possible mixing of populations originated from distinct star-formation episodes. The X-ray data allow the detected sources to be characterized according to hardness ratios, light curves and spectra. Estimates of mass and age were obtained from the 2MASS catalogue, and used to define a complete subsample of stellar counterparts, for statistical purposes. A catalogue of 387 XMM-Newton sources is provided, 78% being confirmed as members or probable members of the CMa R1 association. Flares were observed for 13 sources, and the spectra of 21 bright sources could be fitted by a thermal plasma model. Mean values of fits parameters were used to estimate X-ray luminosities. We found a minimum value of log(L$_X$[erg/s]) = 29.43, indicating that our sample of low-mass stars (M$_\star$ $\leq$ 0.5 M$_\odot$), being faint X-ray emitters, is incomplete. Among the 250 objects selected as our complete subsample (defining our best sample), 171 are found to the East of the cloud, near Z CMa and dense molecular gas, 50% of them being young ( 10 Myr). The opposite happens to the West, near GU CMa, in areas lacking molecular gas: among 79 objects, 30% are young and 50% are older. These findings confirm that a first episode of distributed star formation occurred in the whole studied region ~10 Myr ago and dispersed the molecular gas, while a second, localized episode (< 5 Myr) took place in the regions where molecular gas is still present.
Circular and Linear Regression: Fitting Circles and Lines by Least Squares

Introduction and Historic Overview Classical regression Errors-in-variables (EIV) model Geometric fit Solving a general EIV problem Nonlinear nature of the "linear" EIV Statistical properties of the orthogonal fit Relation to total least squares (TLS) Nonlinear models: general overview Nonlinear models: EIV versus orthogonal fit Fitting Lines Parametrization Existence and uniqueness Matrix solution Error analysis: exact results Asymptotic models: large n versus small sigma Asymptotic properties of estimators Approximative analysis Finite-size efficiency Asymptotic efficiency Fitting Circles: Theory Introduction Parametrization (Non)existence Multivariate interpretation of circle fit (Non)uniqueness Local minima Plateaus and valleys Proof of two valley theorem Singular case Geometric Circle Fits Classical minimization schemes Gauss-Newton method Levenberg-Marquardt correction Trust region Levenberg-Marquardt for circles: full version Levenberg-Marquardt for circles: reduced version A modification of Levenberg-Marquardt circle fit Spath algorithm for circles Landau algorithm for circles Divergence and how to avoid it Invariance under translations and rotations The case of known angular differences Algebraic Circle Fits Simple algebraic fit (Kasa method) Advantages of the Kasa method Drawbacks of the Kasa method Chernov-Ososkov modification Pratt circle fit Implementation of the Pratt fit Advantages of the Pratt algorithm Experimental test Taubin circle fit Implementation of the Taubin fit General algebraic circle fits A real data example Initialization of iterative schemes Statistical Analysis of Curve Fits Statistical models Comparative analysis of statistical models Maximum likelihood estimators (MLEs) Distribution and moments of the MLE General algebraic fits Error analysis: a general scheme Small noise and "moderate sample size" Variance and essential bias of the MLE Kanatani-Cramer-Rao lower bound Bias and inconsistency in the large sample limit Consistent fit and adjusted least squares Statistical Analysis of Circle Fits Error analysis of geometric circle fit Cramer-Rao lower bound for the circle fit Error analysis of algebraic circle fits Variance and bias of algebraic circle fits Comparison of algebraic circle fits Algebraic circle fits in natural parameters Inconsistency of circular fits Bias reduction and consistent fits via Huber Asymptotically unbiased and consistent circle fits Kukush-Markovsky-van Huffel method Renormalization method of Kanatani: 1st order Renormalization method of Kanatani: 2nd order Various "Exotic" Circle Fits Riemann sphere Simple Riemann fits Riemann fit: the SWFL version Properties of the Riemann fit Inversion-based fits The RTKD inversion-based fit The iterative RTKD fit Karimaki fit Analysis of Karimaki fit Numerical tests and conclusions Bibliography Index