Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating cortical thickness trajectories in children across different scanners using transfer learning from normative models

This work illustrates the use of normative models in a longitudinal neuroimaging study of children aged 6-17 years and demonstrates how such models can be used to make meaningful comparisons in longitudinal studies, even when individuals are scanned with different scanners across successive study waves. More specifically, we first estimated a large-scale reference normative model using hierarchical Bayesian regression from N=40,435 individuals across the lifespan and from dozens of sites. We then transfer these models to a longitudinal developmental cohort (N=5,985) with three measurement waves acquired on two different scanners that were unseen during estimation of the reference models. We show that the use of normative models provides individual deviation scores that are independent of scanner effects and efficiently accommodate inter-site variations. Moreover, we provide empirical evidence to guide the optimization of sample size for the transfer of prior knowledge about the distribution of regional cortical thicknesses. We show that a transfer set containing as few as 25 samples per site can lead to good performance metrics on the test set. Finally, we demonstrate the clinical utility of this approach by showing that deviation scores obtained from the transferred normative models are able to detect and chart morphological heterogeneity in individuals born pre-term.
A Review of Six Introductory Texts on Bayesian Methods

Since 1990, Bayesian statistical methods have undergone major advances, both in estimation techniques (especially Markov chain Monte Carlo [MCMC] methods) and in software implementations thereof. During the first decade of this century, several textbooks on Bayesian statistics have appeared, each purporting to introduce Bayesian statistics and the new techniques to students and practitioners. Is a purely or even primarily Bayesian statistical methods curriculum for social science students feasible? Four difficulties impede this prospect:
UvA-DARE (Digital Academic Repository) Extensions of the Virasoro algebra constructed from Kac-Moody algebras using higher order Casimir invariants

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Financial Economics

Using transaction level data from the inter-dealer market, we ﬁnd that the price impact of one standard deviation change in FX swap order ﬂow has increased from less than one basis point prior to 2008 to about ﬁve basis points after 2008. However, the increase in price impact is conﬁned to periods of elevated dispersion in funding costs and over quarterends. Central bank swap lines reduce the order ﬂow into USD, subsequently affecting the FX forward rate. In contrast, over quarter-ends and after monetary policy announcements we observe that dealers immediately adjust prices to curb order ﬂow. © 2022 The Author(s). Published by Elsevier B.V
Grouping axioms for more coherent ontology descriptions

Ontologies and datasets for the Semantic Web are encoded in OWL formalisms that are not easily comprehended by people. To make ontologies accessible to human domain experts, several research groups have developed ontology verbalisers using Natural Language Generation. In practice ontologies are usually composed of simple axioms, so that realising them separately is relatively easy; there remains however the problem of producing texts that are coherent and efficient. We describe in this paper some methods for producing sentences that aggregate over sets of axioms that share the same logical structure. Because these methods are based on logical structure rather than domain-specific concepts or language-specific syntax, they are generic both as regards domain and language.
STUDY ON THE BEHAVIOR OF POLYMERIC FERROCEMENT UNDER IMPACT LOADING

This study concentrates on determining the impact strength of polymeric fiber mesh reinforced ferrocement, under low velocity impact load. The Low-velocity impact study has been conducted on 250 mm square ferrocement slabs. The concept of using polymeric wire mesh is to reduce the corrosion of iron wire mesh, which is one of the major reasons for deterioration of ferrocement. The test procedure has been conducted on fifty four specimens including four different types of iron wire mesh and two types of polymeric mesh, with varying mesh layers from one to three. Results emphasized that the impact energy absorption increases with the raise in the number of polymeric mesh layers and the crack widths are least in amount and size compared to the specimens incorporated with iron wire mesh.
Prediction of mechanical property of steel strips using multivariate adaptive regression splines

In recent times, the problem of prediction of properties of a steel strip has attracted enormous attention from different communities such as statistics, data mining, soft computing, and engineering. This is due to the prospective benefits of reduction in testing and inventory cost, increase in yield, and improvement in delivery compliance. The complexity of the problem arises due to its dependency on the chemical composition of the steel, and a number of processing parameters. To predict the mechanical properties of the strip (yield strength, ultimate tensile strength, and Elongation), a model based on multivariate adaptive regression spline has been developed. It is found that the prediction agrees well with the actual measured data.
Fault Diagnosis for Complex Equipment Based on Belief Rule Base with Adaptive Nonlinear Membership Function

Fault diagnosis of complex equipment has become a hot field in recent years. Due to excellent uncertainty processing capability and small sample problem modeling capability, belief rule base (BRB) has been widely used in the fault diagnosis. However, previous BRB models almost did not consider the diverse distributions of observation data which may reduce diagnostic accuracy. In this paper, a new fault diagnosis model based on BRB is proposed. Considering that the previous triangular membership function cannot address the diverse distribution of observation data, a new nonlinear membership function is proposed to transform the input information. Then, since the model parameters initially determined by experts are inaccurate, a new parameter optimization model with the parameters of the nonlinear membership function is proposed and driven by the gradient descent method to prevent the expert knowledge from being destroyed. A fault diagnosis case of laser gyro is used to verify the validity of the proposed model. In the case study, the diagnosis accuracy of the new BRB-based fault diagnosis model reached 95.56%, which shows better fault diagnosis performance than other methods.
Standard and bootstrap confidence intervals for the correlation coefficient

Several articles in the field of psychology have shown simulation results with the bootstrap-percentile method and variants for the (Pearson) correlation coefficient. The overall result was that with non-normal (especially skewed) data, ρ ≠ 0 and small and medium sample sizes, bootstrap methods show poor coverage accuracy. Some of the authors call into question the ability of any bootstrap methods of valid confidence intervals or acceptance regions for testing hypotheses about ρ under these conditions. Simulation results with the iterated bootstrap will be shown, which clearly demonstrate the ability of this bootstrap method to induce valid confidence intervals under all of the above mentioned conditions not only for ρ, but also for the difference of two correlation coefficients and the squared correlation coefficient. Simulations with the point-biserial correlation coefficient show that for ρph ≠ 0, valid confidence intervals can be achieved with the iterated bootstrap only with medium or large sample sizes, depending on the distribution, while the standard method fails even then.
Evaluation of Potential In Vitro Recombination Events in Codon Deoptimized FMDV Strains

Codon deoptimization (CD) has been recently used as a possible strategy to derive foot-and-mouth disease (FMD) live-attenuated vaccine (LAV) candidates containing DIVA markers. However, reversion to virulence, or loss of DIVA, from possible recombination with wild-type (WT) strains has yet to be analyzed. An in vitro assay was developed to quantitate the levels of recombination between WT and a prospective A24-P2P3 partially deoptimized LAV candidate. By using two genetically engineered non-infectious RNA templates, we demonstrate that recombination can occur within non-deoptimized viral genomic regions (i.e., 3′end of P3 region). The sequencing of single plaque recombinants revealed a variety of genome compositions, including full-length WT sequences at the consensus level and deoptimized sequences at the sub-consensus/consensus level within the 3′end of the P3 region. Notably, after further passage, two recombinants that contained deoptimized sequences evolved to WT. Overall, recombinants featuring large stretches of CD or DIVA markers were less fit than WT viruses. Our results indicate that the developed assay is a powerful tool to evaluate the recombination of FMDV genomes in vitro and should contribute to the improved design of FMDV codon deoptimized LAV candidates.
Volatile aromatic compounds in Mexico City atmosphere: levels and source apportionment

Samples of ambient air were simultaneously collected at three different sites of Mexico City in March of 1997 in order to quantify the most abundant volatile aromatic compounds and estimate the source contributions by application of the chemical mass balance model (CMB). Volatile aromatic compounds were around 20 of the total of non-methane hydrocarbons present in morning air samples. The most abundant volatile aromatic species in urban air were toluene and xylenes followed by 1,2,4 trimethylbenzene benzene ethylbenzene, metaethyltoluene, 1,3,5 trimethylbenzene, styrene, npropylbenzene, and isopropylbenzane. Sampling campaigns were carried out at crossroads, a bus station, a parking place, and areas where solvents and petroleum distillates are used, with the objective of determining people's exposure to volatile aromatic compounds. The CMB was applied for estimating the contribution of different sources to the presence of each one of the most abundant aromatic compounds. Motor vehicle exhaust was the main source of all aromatic compounds, especially gasoline-exhaust, although diesel exhaust and asphalt operations also accounted for toluene, xylenes, ethylbenzene, propylbenzenes, and styrene. Graphic arts and paint application had an important impact on the presence of toluene.
Electric-Field Enhancement and Extinguishment of Optical Second-Harmonic Generation Coupled Quantum Asymmetric in Wells

The second-harmonic susceptibilities of asymmetric cbupled quantum wells (ACQW) and compositionally asymmetric coupled quantum wells (CACQW) under the Muence of the applied electric field are investigated theo-y. Analytic forms of the second-harmonic sllsceptibility are derived by using the density mahix formalism. Coupled one-dimemional Schrzidinger equation and Poisson's equation are solved self-consistently to Bnd the subband eigenenergies and the envelope wavefunctions for the ACQW and CACQW struchues. Dipole moment matrix elements for the ACQW and CACQW are evduated from the Lpsulting envelope wavefunctions and e nonlinear opticel effects are pdcted for these two structlues. Bad w the theoretical calculations, the second-harmonic sw&ptlbii of 50 n" and 35 n" can be achieved for the ACQW and the CACQW, respectively. This is more than two orders o€magnitude enhancement as compared to that of the bulk GaAs. By a suitable choice of the composition of CACQW, a novel structure which the second-order nonlinear optical effect can be turned on or off by the applied electric field is proposed based on the results of the theoretical calculation. This phenomenon is attributed to the symmetry restoration of envelope wavefunctions of the CACQW under the quenching electric field F0~. A simple physical made1 to estimate the Foe has also been developed successtully.
Ensemble Modeling of Hydrologic and Hydraulic Processes at One Shot: Application to Kinematic Open-Channel Flow under Uncertain Channel Properties by the Stochastic Method of Characteristics

A stochastic kinematic wave model for open-channel flow under uncertain channel properties is developed. The Fokker-Planck equation (FPE) of the kinematic open-channel flow process under uncertain channel properties is developed by using the method of characteristics. Every stochastic partial differential equation has a one-to-one relationship with a nonlocal Lagrangian-Eulerian FPE (LEFPE). As such, one can develop an LEFPE for the governing equation of any hydrologic or hydraulic process as the physically based stochastic model of the particular process. A linear, deterministic, differential equation in Eulerian-Lagrangian form, LEFPE provides a quantitative description of the evolution of the probability density functions of the state variables of the process at one shot to describe the ensemble behavior of the process instead of the commonly used many Monte Carlo simulations to quantify the same ensemble behavior. Under certain assumptions, the nonlocal LEFPE reduces to the classical local FPE, which .
Weight function theory of dynamic accuracy loss

This paper carries out the research of the weights of the dynamic accuracy loss and weight functions. It uses the theory of grey correlation analysis to obtain the weight functions of accuracy loss of each main structural unit. From the magnitude of each weight, it can get the accuracy loss of the whole system from the accuracy loss of each structural unit. Then, it uses this theory to analyze the accuracy loss of a practical measurement system, and obtains the weights of accuracy loss of each structural unit. The theory of weight function of accuracy loss makes a foundation for further design of equal accuracy measurement systems.
Structural metamorphosis and photophysical properties of thermostable nano- and microcrystalline lanthanide polymer with flexible coordination chains

ABSTRACT Luminescent lanthanide coordination polymer crystals (LCPCs) represent an area of growing interest in materials chemistry owing to their unique and tailorable functional properties. The LCPCs provide a high level of structural tunability, including size- and morphology-dependent properties; therefore, they are promising materials for next-generation phosphors in a wide range of applications such as light emitting diodes. Here, by controlling the morphology of thermostable europium coordination polymer crystals, [Eu(hfa)3(dpbp)]n, hfa: hexafluoroacetylacetonate and dpbp:4,4’-bis(diphenyl phosphoryl) biphenyl), we realized a novel red phosphor with narrow linewidth emission (FWHM = 7.8 nm). The obtained luminescent LCPCs with unique structures were characterized by X-ray diffraction (XRD), scanning transmission electron microscopy (STEM), dynamic light scattering (DLS) and thermogravimetric analysis. Among, them, size tunable crystalline polymer spheres were found to have high internal quantum efficiency (ex., IQE = 79%) and highly thermostability (>300°C), and to exhibit dispersibility in PMMA media. The obtained results on the structural tunability of these materials can be used for the development of synthesis techniques for nanoscale materials based on crystalline lanthanide-based coordination phosphors. GRAPHICAL ABSTRACT
Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature

Abstract. Both the root mean square error (RMSE) and the mean absolute error (MAE) are regularly employed in model evaluation studies. Willmott and Matsuura (2005) have suggested that the RMSE is not a good indicator of average model performance and might be a misleading indicator of average error, and thus the MAE would be a better metric for that purpose. While some concerns over using RMSE raised by Willmott and Matsuura (2005) and Willmott et al. (2009) are valid, the proposed avoidance of RMSE in favor of MAE is not the solution. Citing the aforementioned papers, many researchers chose MAE over RMSE to present their model evaluation statistics when presenting or adding the RMSE measures could be more beneficial. In this technical note, we demonstrate that the RMSE is not ambiguous in its meaning, contrary to what was claimed by Willmott et al. (2009). The RMSE is more appropriate to represent model performance than the MAE when the error distribution is expected to be Gaussian. In addition, we show that the RMSE satisfies the triangle inequality requirement for a distance metric, whereas Willmott et al. (2009) indicated that the sums-of-squares-based statistics do not satisfy this rule. In the end, we discussed some circumstances where using the RMSE will be more beneficial. However, we do not contend that the RMSE is superior over the MAE. Instead, a combination of metrics, including but certainly not limited to RMSEs and MAEs, are often required to assess model performance.
Highly active MgO catalysts for hydrogenation of levulinic acid to γ-valerolactone using formic acid as the hydrogen source

This study presents an evaluation of catalytic performance of unsupported simple oxide catalysts with varying acid-base properties for the vapor phase hydrogenation of levulinic acid (LA) to γ-valerolactone (GVL) using formic acid (FA) in an aqueous medium. Among the different oxides tested MgO catalyst is found to be highly active. Between the MgO prepared by different methods and commercially obtained, the MgO-UBE showed 100% LA conversion and 100% selectivity to GVL at 270°C. The MgO-UBE catalyst favorably allowed the production of γ-valerolactone in the presence of 50 wt% water relative to the amount of a mixture of levulinic acid and formic acid. Based on the catalytic activity and characterization results, it was concluded that the presence of Mg (OH)2 and a higher number of Lewis acid-base pair sites, Mg2+ LCO2− LC are needed to achieve high LA conversion and selectivity to GVL.
Optimization of family functions and parental support in improving student's academic adjustment ability

Changes in learning patterns both before and after the COVID-19 Pandemic require students to have adjustment abilities. The ability of students to adjust academically in blended learning does require not only teachers' support at school but also the role of parents at home. Well-functioning family is also an important supporting environment for students to have an excellent academic adjustment. To assist parents in helping and guiding students in academics, a workshop for parents was carried out to optimize family functions and parental support in improving students' academic adjustment. A total of 15 parents of Junior High School 4 Jatinangor students participated in this activity. Participants were representatives' parents from grades 7 to 9 of junior high school. The results indicate an increase in parental understanding regarding the role of family functions and parental support for students' academic adjustment. Parents also responded well and were satisfied with the materials and activities.
Spectral analysis for physical applications : multitaper and conventional univariate techniques

Glossary of symbols 1. Introduction to spectral analysis 2. Stationary stochastic processes 3. Deterministic spectral analysis 4. Foundations for stochastic spectral theory 5. Linear time-invariant filters 6. Non-parametric spectral estimation 7. Multiple taper spectral estimation 8. Calculation of discrete prolate spheroidal sequences 9. Parametric spectral estimation 10. Harmonic analysis References Appendix: data and code via e-mail Index.
Regeneration of pavement surface textures using M‐sigmoid‐normalized generative adversarial networks

The high cost of collecting surficial textures has been the bottleneck problem for many decades. To bridge this gap, this study aims to propose a complete framework based on the generative adversarial networks (GANs) architecture for texture regeneration using limited texture data samples. Four variants of the GAN were compared to achieve the best regeneration performance. Prior to running GAN, specifically improved data augmentation and modified sigmoid normalization operations were dedicated to avoiding the loss of texture information and the non‐convergence problem. After running GAN, the estimation metrics were introduced and discussed separately to quantitatively evaluate the rationality and diversity of the regenerated textures. The results demonstrated that the use of improved data augmentation and normalization methods significantly enhanced the regeneration capability of GAN, and more importantly the skewed distribution of surficial heights which is not achievable by present texture regeneration methods was most effectively regenerated by deep regret analytic GAN with well generalization ability. Our study provides a promising choice to generate virtually realistic pavement surface textures.
CHARACTERIZATION OF (CdSe)ZnS CORE-SHELL QUANTUM DOTS IN MICRODROP LASER CAVITY

Lasing behavior of water soluble (CdSe)ZnS core-shell quantum dots (QD) has been investigated in a spherical liquid microdrop cavity. We have estimated the minimum volume fraction of QD necessary for lasing as 9.27 ×10-6 and emission cross section of the QDs as 4.5 ×10-15 cm2. The microdrop liquid cavity has been characterized with the help of rhodamine 6G (Rh6G) dye and we found its cavity Q factor in whispering gallery mode (WGM) resonance to be 1.4 ×104.