Miracle-dz/UniFAR-FTUs huggingface dataset:
Oxygen Isotopic Exchange between Amorphous Silicate and Water Vapor and Its Implications for Oxygen Isotopic Evolution in the Early Solar System

Meteoritic evidence suggests that oxygen isotopic exchange between 16O-rich amorphous silicate dust and 16O-poor water vapor occurred in the early solar system. In this study, we experimentally investigated the kinetics of oxygen isotopic exchange between submicron-sized amorphous forsterite grains and water vapor at protoplanetary disk-like low pressures of water vapor. The isotopic exchange reaction rate is controlled either by diffusive isotopic exchange in the amorphous structure or by the supply of water molecules from the vapor phase. The diffusive oxygen isotopic exchange occurred with a rate constant D (m2 s−1) = (1.5 ± 1.0) × 10−19 exp[−(161.5 ± 14.1 (kJ mol−1))R−1(1/T−1/1200)] at temperatures below ∼800–900 K, and the supply of water molecules from the vapor phase could determine the rate of oxygen isotopic exchange at higher temperatures in the protosolar disk. On the other hand, the oxygen isotopic exchange rate dramatically decreases if the crystallization of amorphous forsterite precedes the oxygen isotopic exchange reaction with amorphous forsterite. According to the kinetics for oxygen isotopic exchange in protoplanetary disks, original isotopic compositions of amorphous forsterite dust could be preserved only if the dust was kept at temperatures below 500–600 K in the early solar system. The 16O-poor signatures for the most pristine silicate dust observed in cometary materials implies that the cometary silicate dust experienced oxygen isotopic exchange with 16O-poor water vapor through thermal annealing at temperatures higher than 500–600 K prior to their accretion into comets in the solar system.
A Geometric Approach to Visualization of Variability in Univariate and Multivariate Functional Data

This dissertation describes a new method for the construction and visualization of geometrically-motivated displays for univariate functional data and multivariate curve data. For univariate functional data, we use a recent functional data analysis framework, based on a representation of functions called square-root slope functions. We decompose observed variation in functional data into three main components: amplitude, phase, and vertical translation. For multivariate curve data, we use a similar recent elastic curve data analysis framework, based on square-root velocity functions, to decompose variability in curve data into five main components: location, scale, shape, orientation, and reparametrization. We then construct separate displays for each component, using the geometry and metric of each representation space, based on a novel definition of the median, the two quartiles, and extreme observations. The outlyingness of function and curve data is a very complex concept. Thus, we propose to separately identify outliers based on each of the main components after decomposition. We provide a variety of visualization tools for the proposed displays, including surface plots for the amplitude and phase components of univariate functional data, and circular plots for the orientation and seed components of bivariate curve data, among others. We evaluate the proposed methods using extensive simulations and then focus our attention on multiple real data applications, including exploratory data analysis of sea surface temperature functions, electrocardiogram biosignals, growth ii curves, gait functions, and respiration functions. We also study variability in simulated 3D spirals, handwritten signatures, 3D fibers from Diffusion Tensor Magnetic Resonance Imaging (DT-MRI), and 3D Lorenz attractor curves.
East Asia Reanalysis System (EARS)

Abstract. Reanalysis data play a vital role in weather and climate study as well as meteorological resource development and application. In this work, the East Asia Reanalysis System (EARS) was developed using the Weather Research and Forecasting (WRF) model and the Gridpoint Statistical Interpolations (GSI) data assimilation system. The regional reanalysis system is forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) global reanalysis ERA-Interim data at 6 h intervals. Hourly surface observations are assimilated by the Four-Dimension Data Assimilation (FDDA) scheme during the WRF model integration; upper observations are assimilated in three-dimensional variational data assimilation (3D-VAR) mode at the analysis moment. It should be highlighted that many of the assimilated observations have not been used in other reanalysis systems. The reanalysis runs from 1980 to 2018, producing a regional reanalysis dataset covering East Asia and surrounding areas at 12 km horizontal resolution, 74 sigma levels, and 3 h intervals. Finally, an evaluation of EARS has been performed with respect to the root mean square error (RMSE), based on the 10-year (2008–2017) observational data. Compared to the global reanalysis data of ERA-Interim, the regional reanalysis data of EARS are closer to the observations in terms of RMSE in both surface and upper-level fields. The present study provides evidence for substantial improvements seen in EARS compared to the ERA-Interim reanalysis fields over East Asia. The study also demonstrates the potential use of the EARS data for applications over East Asia and proposes further plans to provide the latest reanalysis in real-time operation mode. Simple data and updated information are available on Zenodo at https://doi.org/10.5281/zenodo.7404918 (Yin et al., 2022), and the full datasets are publicly accessible on the Data-as-a-Service platform of the China Meteorological Administration (CMA) at http://data.cma. cn (last access: 19 May 2023).
Testing for moderate explosiveness

SummaryThis paper considers a moderately explosive AR(1) process where the autoregressive root approaches unity from the right at a certain rate. We first develop a test for the null of moderate explosiveness under independent and identically distributed errors. We show that the t statistic is asymptotically standard normal regardless of whether the true process is dominated by the stochastic moderately explosive trend or the deterministic nonlinear drift trend. This result is in sharp contrast with the existing literature, wherein nonstandard limiting distributions are obtained under different model assumptions. When the errors are weakly dependent, we show that the t statistic based on a heteroskedasticity and autocorrelation robust standard error follows Student’s t distribution in large samples. Monte Carlo simulations show that our tests have satisfactory size and power performances in finite samples. Applying the asymptotic t test to ten major stock indexes in the pre-2008 financial exuberance period, we find that most indexes are only mildly explosive or not explosive at all, which implies that the bout of the irrational rise was not as serious as previously thought.
Circulation conservation and vortex breakup in magnetohydrodynamics at low magnetic Prandtl number

In this paper we examine the role of weak magnetic fields in breaking Kelvin’s circulation theorem and in vortex breakup in two-dimensional magnetohydrodynamics for the physically important case of a fluid with low magnetic Prandtl number (low $Pm$ ). We consider three canonical inviscid solutions for the purely hydrodynamical problem, namely a Gaussian vortex, a circular vortex patch and an elliptical vortex patch. We examine how magnetic fields lead to an initial loss of circulation $\unicode[STIX]{x1D6E4}$ and attempt to derive scaling laws for the loss of circulation as a function of field strength and diffusion as measured by two non-dimensional parameters. We show that for all cases the loss of circulation depends on the integrated effects of the Lorentz force, with the patch cases leading to significantly greater circulation loss. For the case of the elliptical vortex, the loss of circulation depends on the total area swept out by the rotating vortex, and so this leads to more efficient circulation loss than for a circular vortex.
Penalized least squares smoothing of two-dimensional mortality tables with imposed smoothness

ABSTRACT This paper presents a method to estimate mortality trends of two-dimensional mortality tables. Comparability of mortality trends for two or more of such tables is enhanced by applying penalized least squares and imposing a desired percentage of smoothness to be attained by the trends. The smoothing procedure is basically determined by the smoothing parameters that are related to the percentage of smoothness. To quantify smoothness, we employ an index defined first for the one-dimensional case and then generalized to the two-dimensional one. The proposed method is applied to data from member countries of the OECD. We establish as goal the smoothed mortality surface for one of those countries and compare it with some other mortality surfaces smoothed with the same percentage of two-dimensional smoothness. Our aim is to be able to see whether convergence exists in the mortality trends of the countries under study, in both year and age dimensions.
Teacher’s instruction in the reflection phase of the problem solving process

Mathematical problem solving has a key part in developing students' mathematical thinking. Yet in the Finnish primary school classrooms mathematics lessons are very traditional and have little room for problem solving and mathematical discussions. Although problem solving has been a part of the Finnish curriculum for a few decades, it is the teachers who seem to choose not to include problem solving in the classroom on a regular basis. In this article I take a look at three Finnish fifth grade teachers who took part in a study on problem solving. They each incorporated problem solving in their mathematics lessons approximately once a month, and in this study I focused on one of the problems - an open problem called "The Labyrinth". In each lesson I chose to focus on the teachers' instruction in the reflection phase of the problem solving process. When instructing individual students in the reflection phase and during whole-classroom discussions, the teacher has an opportunity to point out the important parts of the problem solving process, help the students make connections and recall key moments of the process. In the reflection phase there is an opportunity to reflect, review and analyze one's solutions and make generalizations. In the Labyrinth problem the teacher's own understanding of the solution was an important factor during the instruction and the whole-classroom discussion. If the teacher's instruction was purely led by the students' own discoveries and insights, some important points were left unexplored. The teacher can even lead the students to the wrong direction, if he or she hasn't carefully thought through the solution of the problem beforehand. The problem solving lesson is not just about finding a suitable problem and presenting it to the students, but guiding the students in the process.
Eagle owls’ predation within a highly diversified Late Glacial landscape: remains of pikas and hares (Lagomorpha) from the Loutra Almopias Cave (Central Macedonia, Greece)

During cave bear excavations in the Loutra Almopias Cave, Pella District, in Central Macedonia, Greece, an ecologically highly diverse Late Glacial faunal assemblage, mainly micromammals and birds, was sampled from an elevated small niche labelled LAC Ia. The lagomorphs are represented by steppe pika (Ochotona pusilla), brown (or European) hare (Lepus europaeus) and mountain hare (Lepus timidus). The site evidences the first record of this last species in Greece and its southernmost evidence so far. The taphonomic patterns of the fossils refer to eagle owls (Bubo bubo) as an accumulating agent. This is congruent with the total LAC Ia species spectrum and the bone element abundance and destruction patterns. Radiocarbon dates of 12,350±40 14C yrs BP (VERA-5631) from a Lepus sp. bone and 16,427±96 14C yrs BP (VERA-7402) from a L. timidus premolar indicate the emplacement of the assemblage in the (very probably early phase of the) Late Glacial. The taphocoenosis reflects a high variety of habitats and biodiversity from periglacial alpine grassland to deciduous forests and Mediterranean open fore-land areas with scattered brush and thick scrub. The position of the eagle owl site is approximately 50 m inside the cave. Along the distance from the Late Pleistocene entrance, the nocturnal raptors had to manage two direction changes within their flight path. That opening was closed later by talus sediments, and thus the fossil owl nest or feeding place has been sealed. The LAC Ia assemblage is so far a unique terrestrial record of Late Glacial biota in the Southern Balkans.
Forgiveness in Adolescents Post-Divorce Parents in the Makassar Bugis Tribe

This study aims to find out the description of forgiveness in post-divorce adolescents in the Bugis-Makassar tribe. The research methodology used is quantitative. The subjects of this study were adolescents aged 12-18 years, ethnic Bugis or Makassar, and whose parents were divorced. There were 179 subjects in this study consisting of 66 men and 113 women. The measurement tool used in this study is the Transgression-Related Interpersonal Motivations Inventory (TRIM-18) to measure forgiveness with a reliability of 0.738. This study uses descriptive analysis techniques with the help of SPSS 25 for Windows software. The results of this study indicate that there are 147 (82.1%) students who have high forgiveness, as many as 31 (17.3%) students who have moderate forgiveness and as many as 1 (0.6%) subject with low forgiveness. This study concludes that the forgiveness of post-divorce adolescents in the Bugis-Makassar tribe is at a high level and most adolescents who have not been able to forgive their parents because they want to take revenge on their parents.
Efficient algorithms for least squares wave equation migration and source signature estimation

Estimating accurate images of the subsurface is one of the end products of seismic data processing. Numerical solutions to the wave equation allow designing linearized forward operators. The adjoint of the linearized forward operator is used to image the interior of the earth. The adjoint operator (migration operator) is sensitive to data sampling and background velocity model. Likewise, migration via adjoint operators produces low-resolution images of the subsurface. Posing seismic imaging as an inverse problem leads to a procedure where the inversion of the linearized forward modelling operator can retrieve an image that honours the seismic observations. Formulating imaging as an inverse problem, besides, allows one to include model space constraints to improve the quality and resolution of subsurface images. This thesis concentrates on the development of efficient and accurate methods for linearized imaging also called least-squares migration. Developing efficient algorithms for least-squares migration is a vital step in better understanding the earth’s subsurface structure. However, computational requirements and proper data conditioning are some of the barriers that prevent least-squares migration from becoming a routinely used processing workflow. As part of the development of practical algorithms for least-squares migration, we took advantage of adaptive signal processing strategies and the computational efficiency of preconditioning techniques. We develop scalable algorithms for least-squares migration with less memory and
Arithmetic properties of bipartitions with ℓ-core

Abstract Let Aℓ(n) denote the number of bipartitions of n with ℓ-core. In this paper, we prove a theorem on congruences modulo 2 for Aℓ(n) with ℓ≥2 by employing a well known congruence due to binomial theorem. Also, we show some interesting congruences for some special ℓ’s.
The Analysis of Risk Measurement and Association in China’s Financial Sector Using the Tail Risk Spillover Network

This study focused on analyzing the complexities and risk spillovers that arise among financial institutions due to the development of financial markets. The research employed the conditional value at risk (CoVaR) methodology to quantify the extent of tail risk spillover and constructed a risk spillover network encompassing Chinese financial institutions. The study further investigated the characteristics, transmission paths, and dynamic evolution of this network under different risk conditions. The empirical findings of this research highlighted several important insights. First, financial institutions play distinct roles in the risk spillover process, with the securities and banking sectors as risk exporters and the insurance and diversified financial sectors as risk takers. The closest risk spillover relationships were observed between banking and insurance and between securities and diversified financial sectors. Second, in high-risk scenarios, there is significant intrasectoral risk transmission between banks and the diversified financial sector, as well as dual-sectoral risk contagion between banks and securities, with the most-common transmission occurring between diversified financial and securities sectors. Finally, the securities sector acts as the pivotal node for risk spillovers, being the main transmitter of intersectoral risks. The formation and evolution of risk spillover networks are influenced by endogenous mechanisms, in particular the convergence effect.
The Compatibility of Preoperative Temporal Bone CT Scan Interpretation and Intraoperative Findings in Chronic Suppurative Otitis Media at Dr. Zainoel Abidin Hospital Banda Aceh

Introduction: Chronic suppurative otitis media (CSOM) is middle ear and mastoid infection that causes hearing loss globally. Computed Tomography (CT)-Scan of the temporal bone is useful for assessing the pathogenesis of the disease and estimating the prognosis. In addition, evaluation of CT-Scan in patients with CSOM is useful for selecting the appropriate surgical procedure to minimize post-surgical complications. This study aims to assess the suitability of temporal CT-Scan interpretation to intraoperatif findings in CSOM patients. Methods: This is an observational study with cross-sectional design conducted at the dr. Zainoel Abidin General Hospital, Banda Aceh. The components of suitability evaluation include cholesteatoma, scutum erosion, ossicles, tegmen tympani, facial canal, posterior wall and sigmoid sinus wall. The interpretation suitability of temporal CT-Scan and intraoperatif findings was performed using the Kappa test. Results: A total of 18 CSOM patients were involved in this study with a mean age of 32.44 years and dominated by the safe type with a percentage of 55.6%. Interpretation of ossicular erosion based on temporal CT scan has very strong suitability with the intraoperatif findings with k=0.88 followed by posterior wall erosion (k=0.684), scutum erosion (k=0.679), tympanic tegmen erosion (k=0.455) and facial canal erosion (k=0.341). The findings of cholesteatoma and erosion of the sigmoid sinus wall had a very low suitability (k<0.001). Conclusion: Temporal CT scan in CSOM patients has relatively good suitability with intraoperatif findings in evaluating erosion of the ossicles, posterior wall, and scutum. Another examination modality is necessary to assess and improve the accuracy of disease pathogenesis.
Harris-Hawk-Optimization-Based Deep Recurrent Neural Network for Securing the Internet of Medical Things

The healthcare industry has recently shown much interest in the Internet of Things (IoT). The Internet of Medical Things (IoMT) is a component of the IoTs in which medical appliances transmit information to communicate critical information. The growth of the IoMT has been facilitated by the inclusion of medical equipment in the IoT. These developments enable the healthcare sector to interact with and care for its patients effectively. Every technology that relies on the IoT can have a serious security challenge. Critical IoT connectivity data may be exposed, changed, or even made unavailable to authenticated users in the case of such attacks. Consequently, protecting IoT/IoMT systems from cyber-attacks has become essential. Thus, this paper proposes a machine-learning- and a deep-learning-based approach to creating an effective model in the IoMT system to classify and predict unforeseen cyber-attacks/threats. First, the dataset is preprocessed efficiently, and the Harris Hawk Optimization (HHO) algorithm is employed to select the optimized feature. Finally, machine learning and deep learning algorithms are applied to detect cyber-attack in IoMT. Results reveal that the proposed approach achieved an accuracy of 99.85%, outperforming other techniques and existing studies.
OSTEOMETRIC MORPHOMETRY OF PROXIMAL TIBIAL END IN INDIAN POPULATION: A FORENSIC POINT OF VIEW WITH ITS CLINICAL IMPORTANCE

Objectives: Considering the importance of sexual dimorphism to the identification of skeletons for scientific, medical and forensic purposes, the aim of the present study was to investigate the gender of the person based on morphometric aspects of the proximal end of tibia in Indian population. Material and Method: This prospective descriptive study was carried out on 385 dry, adult tibias, which were collected from the department of Anatomy department of a medical college in north India. 385 fully ossified and processed dry bones were used to study. Unossified, injured or anomalous tibia bones were excluded from the study. Proximal end of tibia is studied under various parameters. After obtaining the values of the all parameters, data is corelated with the record section of the bone bank of the particular medical college. Result: It shows that, there is significant difference between male and female parameters and all results were statistically significant. Conclusion: This study will help to provide a basis for application in forensic science, in prosthesis, and in clinical practice also.
Number identification: a unique developmental pathway in mathematics?

ABSTRACT We make a prima facie case for identifying a single pathway in the learning of Hindu-Arabic numerical symbols and discuss why this ability may be a critical gateway concept in developing mathematical competencies. A representative sample of English and Scottish children was assessed using a number symbol identification paradigm in the Performance Indicators in Primary Schools (PIPS) Baseline assessment at the beginning and end of their first school year. Through a Rasch analysis of real and simulated data, we show that: (1) there appears to be a single, unidimensional pathway in learning to identify number symbols with discrete difficulty stages, (2) on examination of differential item functioning, this pathway is invariant across gender, country, socio-economic background, first language and across the first year of schooling and (3) almost all children make progress along the pathway during the year. A number identification scale may thus be a universal ruler by which all pupils could be assessed.