Miracle-dz/UniFAR-FTUs huggingface dataset:
Tritium Counting Using a Europium Coordination Complex

Abstract The luminescence of Eu(DPA)3 3- induced by beta particles from tritium decay was measured. The solution of Eu3+ was prepared with europium(III) nitrate hexahydrate and was mixed with a DPA (2, 6-pyridinedicarboxylic acid or dipicolinic acid) solution of pH 11 to yield Eu(DPA)3 3-. The formation of Eu(DPA)3 3- was confirmed through spectrometry. Tritiated water was added to the prepared solution of Eu(DPA)3 3-. The luminescence intensity is proportional to the amount of tritium. In this paper we demonstrate the potential of this Eu complex as an inorganic liquid scintillator.
Turbulence in intermittent transitional boundary layers and in turbulence spots

Direct numerical simulation data of bypass transition in flat-plate boundary layers are analysed to examine the characteristics of turbulence in the transitional regime. When intermittency is 50 % or less, the flow features a juxtaposition of turbulence spots surrounded by streaky laminar regions. Conditionally averaged turbulence statistics are evaluated within the spots, and are compared to standard time averaging in both the transition region and in fully turbulent boundary layers. The turbulent-conditioned root-mean-square levels of the streamwise velocity perturbations are notably elevated in the early transitional boundary layer, while the wall-normal and spanwise components are closer to the levels typical for fully turbulent flow. The analysis is also extended to include ensemble averaging of the spots. When the patches of turbulence are sufficiently large, they develop a core region with similar statistics to fully turbulent boundary layers. Within the tip and the wings of the spots, however, the Reynolds stresses and terms in the turbulence kinetic energy budget are elevated. The enhanced turbulence production in the transition zone, which exceeds the levels from fully turbulent boundary layers, contributes to the higher skin-friction coefficient in that region. Qualitatively, the same observations hold for different spot sizes and levels of free-stream turbulence, except for young spots which do not yet have a core region of developed turbulence.
A segmented subreflector with electroformed nickel laminated panels for the Large Millimeter Telescope

The Large Millimeter Telescope (LMT) Alfonso Serrano is a 50 m diameter single-dish radio telescope optimized for astronomical observations at wavelengths of about a millimeter. Built and operated by the Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE) in collaboration with the University of Massachusetts (UMASS), the telescope is located at the 4600 m summit of volcano Sierra Negra, Mexico. Anticipating the completion of the main reflector, currently operating over a 32 m subaperture, INAOE has contracted Media Lario for the design and manufacturing of a new 2.63 m subreflector that will enable higher efficiency astronomical observations with the entire main reflector surface. The new subreflector manufactured by Media Lario is segmented in 9 smaller panels, one central dome and eight identical petals, assembled and precisely aligned on a steel truss structure that will be connected to the hexapod mounted on the tetrapod head. Each panel was fabricated with Media Lario’s unique laminated technology consisting of front and rear Nickel skins, electroformed from precise molds and bonded to a lightweight Aluminum honeycomb core. The reflecting surface of each panel was given a thin galvanic Rhodium coating that ensures that the reflector survives the harsh environmental conditions at the summit of Sierra Negra during the 30 year lifetime of the telescope. Finally, the 2.63 m subreflector produced by Media Lario was qualified for typical cold night through hot day observation conditions with a maximum RMS error of 24.8 μm, which meets INAOE’s requirements.
Analysis of environmental literacy and awareness to maintain environmental sustainability

Environmental damage is the effect of negative impacts on the natural environment caused by human activities. The importance of empowering knowledge and caring for the environment in students so that they can participate in protecting and preserving the environment. The purpose of this research is to describe literacy and environmental awareness to preserve the environment and the relationship between environmental literacy and awareness to preserve the environment. This research method uses descriptive quantitative research and research techniques using a questionnaire with a sample of 50 students using a random sampling technique in the Adiwiyata school program, especially junior high school students. The instruments used were student characteristic sheets, environmental literacy, and environmental awareness questionnaires. Research data were analyzed descriptively and the relationship between literacy and environmental awareness used correlation analysis using SPSS. The results showed that students' environmental literacy was classified as moderate to high with a score of 1.6 – 3.20. The average value of students' environmental awareness is 73% indicating that students have a caring attitude toward environmental problems. Environmental attitudes and environmental awareness also have a significant relationship (sig <0.05). Through environmental literacy and awareness, students will have the potential to protect and preserve the environment.
The comparative effects of cumulative and unitary SAFMEDS terms in an introductory undergraduate behavior analysis course

ABSTRACT Research in precision teaching (PT) and verbal behavior has implications for undergraduate instruction, but effects of PT for under-graduate coursework are not yet fully understood. The authors examined the differences between learning outcomes for Say All Fast Minute Every Day Shuffled (SAFMEDS) cards between cumulative decks where all terms were practiced (fall semester) and unitary decks where terms were split into 10 units with no more than 10 cards each (spring semester). Results showed that the rate of correct terms recited per minute increased over the course of both semesters, the rate of incorrect terms decreased, and the rate of skips remained variable. The changes in rate occurred more quickly throughout the spring semester and more students reached the frequency aims. Other factors examined included timing intervals, multiple checkouts, definition length, and retention. The results have implications for the use of PT, especially SAFMEDS, in college classrooms.
A Novel Wrapped Feature Selection Framework for Developing Power System Intrusion Detection Based on Machine Learning Methods

The power system measurement data has high-dimensional features and strong noise, which is difficult to be directly used for intrusion detection. Traditional machine learning methods used in the power system intrusion detection take the feature processing as a preprocessing step and perform separately from the training, which makes the features not well adapted to the training. Therefore, this article proposes a novel binary particle swarm-wrapped feature selection optimization framework (BPSWO), which can improve the intrusion detection accuracy of machine learning methods by strengthening the coupling between the feature selection and the training. First, the improved transfer function is used to make the method converge to the global optimal particle. Second, the chaotic transformation and the Hamming distance are used to solve the premature problem of the traditional particle swarm optimization. Then, the different classifiers can be embedded in the particle swarm for training. The BPSWO trains the classifier while selecting features and the final training classifier is used for intrusion detection. The proposed method is examined on the public power system from Oak Ridge National Laboratory, USA and the IEEE 57-bus system. Compared with the existing power system intrusion detection methods based on machine learning, the experimental results show that the BPSWO can achieve the state-of-the-art in the detection accuracy, which proves the effectiveness and stability of the proposed method.
Derivation of Semiclassical Kinetic Theory in the Presence of Non-Abelian Berry Curvature

In quantum mechanics it is often required to describe in a semiclassical approximation the motion of particles moving within a given energy band. Such a representation leads to the appearance of an analogues of fictitious forces in the semiclassical equations of motion associated with the Berry curvature. The purpose of this paper is to derive systematically the kinetic Boltzmann equations displaying these effects in the case that the band is degenerate, and as such the Berry curvature is non-Abelian. We use the formalism of phase-space quantum mechanics to derive the results.
Regression calibration utilizing biomarkers developed from high-dimensional metabolites

Addressing systematic measurement errors in self-reported data is a critical challenge in association studies of dietary intake and chronic disease risk. The regression calibration method has been utilized for error correction when an objectively measured biomarker is available; however, biomarkers for only a few dietary components have been developed. This paper proposes to use high-dimensional objective measurements to construct biomarkers for many more dietary components and to estimate the diet disease associations. It also discusses the challenges in variance estimation in high-dimensional regression methods and presents a variety of techniques to address this issue, including cross-validation, degrees-of-freedom corrected estimators, and refitted cross-validation (RCV). Extensive simulation is performed to study the finite sample performance of the proposed estimators. The proposed method is applied to the Women's Health Initiative cohort data to examine the associations between the sodium/potassium intake ratio and the total cardiovascular disease.
Understanding of the Effect of the Adsorption of Atom and Cluster Silver on Chitosan: An In Silico Analysis

In this work, the structural, electronic, and optical stability properties of the chitosan monomer (M-Ch) and atomic silver complex are reported, as well as a unitary cell of a silver cluster in the gas phase and acetic acid. The generalized gradient approximation HSEh1PBE/def2-TZVPP50 results established the structures’ anionic charge (Q = −1|e|) and the doublet state (M = 2). The high cohesive energy indicates structural stability, and the quantum-mechanical descriptors show a high polarity and low chemical reactivity. Also, the quantum-mechanical descriptors present a low work function that shows the structures are suitable for applications in light-emitting diodes. Finally, the electronic behavior observed by the |HOMO-LUMO| gap energy changes depending on the atomic silver incorporated into the complex.
Comparative analysis of gut DNA viromes in wild and captive Himalayan vultures

Introduction Himalayan vultures (Gyps hinalayensis) are widely distributed on the Qinghai-Tibetan Plateau and play a crucial role in maintaining the ecological balance by feeding on decayed corpses of wild and domestic animals. Large-scale culture and metagenomics studies have broadened our understanding of viral diversity in animals’ gastrointestinal tracts. However, despite the importance of gut viral communities in regulating bacterial diversity and performing symbiotic functions, no gut viral study has been conducted on Himalayan vultures. Furthermore, the impact of captivity on the gut virome of these vultures remains unknown. Methods In this study, metagenomic sequencing methods targeting DNA of virus-like particles enriched from feces were used to characterize the gut DNA viromes of wild and captive Himalayan vultures. Results In total, 22,938 unique viral operational taxonomic units (vOTUs) were identified and assigned to 140 viral genera in 41 viral families. These families included viruses associated with bacteria, animals, plants, insects, and archaea. Phage communities, including Siphoviridae, Microviridae, Myoviridae, Inoviridae, and Herelleviridae, dominated the gut virome of Himalayan vultures. Wild vultures exhibited higher viral richness and diversity compared with those in captivity. The functional capacity of the gut virome was characterized by identifying 93 KEGG pathways, which were significantly enriched in metabolism and genetic information processing. Abundant auxiliary metabolic genes, such as carbohydrate-active enzyme, and antibiotic resistance genes, were also found in the vultures’ gut virome. Discussion Our findings reveal the complex and diverse viral community present in the gut virome of Himalayan vultures, which varies between wild, and captive states. The DNA virome dataset establishes a baseline for the vultures’ gut virome and will serve as a reference for future virus isolation and cultivation. Understanding the impact of captivity on the gut virome contributes to our knowledge of vultures’ response to captivity and aids in optimizing their rehabilitation and implementing protective measures.
Heitler-Matthews model with leading-particle effect

It is well known that the Heitler model and its extensions (like the Heitler-Matthews model) describe qualitatively many fundamental properties of extensive air showers initiated in the atmosphere by the high-energy cosmic rays. Typically, only the secondary particle multiplicity and the fraction of neutral-to-charged pions are considered as analytically treatable parameters of hadronic interactions. Other relevant parameters of hadronic interactions such as inelasticity and the lifetime of the leading particle are taken into account only in detailed Monte Carlo simulations. Here we present an extension of the Heitler-Matthews model that includes the leading particle effect and analytically derive the number of muons produced in air showers in a self-consistent way. In a second step we apply this model to calculate the dependence of the depth of the shower center-of-gravity on various model parameters. In this way, we obtain predictions for the depth of shower maximum, which is a well known observable sensitive to the mass of primary particles and is regularly used in cosmic-ray research.
A Bayesian approach for a zero modified Poisson model to predict match outcomes applied to the 2012–13 La Liga season

In any sports competition, strong interest is devoted to the knowledge on the team that will be champion. The result of a match, the chance of a team either qualifying for a speciﬁc tournament, or relegating, the best attack and defense are all topics of interest. This paper presents a Bayesian methodology for modeling the number of goals scored by a team based on Zero-Modiﬁed Poisson distribution. An important advantage of this distribution is the ﬂexibility in modeling count data without previous knowledge of the sampling characteristic with respect to the frequency of zeros (inﬂated, standard, deﬂation). These characteristics are present in the data sets referring to the number of goals scored by different teams. Inference procedures and computational simulation studies are also discussed. The proposed methodology was applied to the 2012–13 La Liga and the results were compared with those of the Poisson model using the De Finetti measure an percentage of correct predictions. a
Environmental management implementation in wastewater treatment at a machine-building enterprise: From theory to practice

This study examines environmental management implementation in the context of wastewater treatment at machine-building enterprises. The article aims to assess how effectively environmental management is used in the wastewater treatment system to ensure rational resource use. It is noted that wastewater contains a significant amount of various pollutants that must be removed before disposal. A wastewater samples analysis was carried out to assess the environmental management implementation’s effectiveness. The changes in the concentration of the pollutants during three months were found: the hydrogen indicator decreased from 7.83 mg/dm3 to 7.58 mg/dm3. The oil product concentration increased from 22.2 mg/dm3 to 3.4 mg/dm3, while the fat concentration remained stable. The received results provide important information for improving the wastewater treatment system and environmental management implementation. To ensure environmental safety and compliance with environmental standards, it is necessary to implement environmental management in wastewater treatment at machine-building enterprises. The optimal wastewater treatment technology choice and monitoring program development are described. The article contains practical recommendations for the implementation of environmental management at a machine-building enterprise and a perspective on this direction of development. The research is relevant and useful for machine-building complexes that have problems with wastewater treatment and aim to implement environmental management.
Adaptive Multiple Shooting for Boundary Value Problems and Constrained Parabolic Optimization Problems

Subject of this thesis is the development of adaptive techniques for multiple shooting methods. The focus is on the application to optimal control problems governed by parabolic partial differential equations. In order to retain as much freedom as possible in the later choice of discretization schemes, the details of both direct and indirect multiple shooting variants are worked out on an abstract function space level. Therefore, shooting techniques do not constitute a way of discretizing a problem. A thorough examination of the connections between the approaches provides an overview of different shooting formulations and enables their comparison for both linear and nonlinear problems. We extend current research by considering additional constraints on the control variable in the multiple shooting context. An optimization problem is developed which includes so-called box constraints in the multiple shooting context. Several modern algorithms treating control constraints are adapted to the requirements of shooting methods. The modified algorithms permit an extended comparison of the different shooting approaches. The efficiency of numerical methods can often be increased by developing grid adaptation techniques. While adaptive discretization schemes can be readily transferred to the multiple shooting context, questions of conditioning and stability make it difficult to develop adaptive features for shooting point distribution in multiple shooting processes. We concentrate on the design and comparison of two different approaches to shooting grid adaptation in the framework of ordinary differential equations. A residual-based adaptive algorithm is transferred to parabolic optimization problems with control constraints. The presented concepts and methods are verified by means of several examples, whereby theoretical results are numerically confirmed. We choose the test problems so that the simple shooting method becomes unstable and therefore a genuine multiple shooting technique is required.
Angle dependence of strong-field single and double ionization of carbonyl sulfide

We have studied, experimentally and theoretically, the ionization probability of carbonyl sulﬁde (OCS) molecules in intense linearly-polarized 800 nm laser pulses as a function of the angle between the molecular axis and the laser polarization. Experimentally, the molecules are exposed to two laser pulses with a relative time delay. The ﬁrst, weaker pulse induces a nuclear rotational wave packet within each molecule such that the ensemble exhibits preferential alignment in the labora-tory frame at speciﬁc times. The second, stronger pulse induces ionization, and the variation in single and double ionization yields is measured as a function of the delay between the two pulses. The angular-dependence of the ionization yield is extracted by ﬁtting the delay-dependent yields to a sum of delay-dependent moments of the rotational wave packet’s angular distribution. We compute these same angular-dependent strong-ﬁeld ionization yields for OCS using time-dependent density functional theory (TDDFT). For the single ionization case, our measurements agree well with TDDFT calculations and with previous experiments. Furthermore, analysis of the simulated one-body density reveals that, when averaged over a laser cycle, the resulting hole is delocalized across the molecule for light polarized perpendicular to the molecular axis, and mostly localized on the sulfur for parallel polarization. This suggests that preferential molecular alignment is a key parameter for controlling charge migration dynamics initiated by strong-ﬁeld ionization. For double ionization, the agreement between experiment and theory is less compelling, reﬂecting the substantial challenges of computing double ionization yields using TDDFT methods.
The Underappreciated Benefits of Interleaving for Category Learning

The present study examined the effects of study schedule (interleaving vs. blocking) and feature descriptions on category learning and metacognitive predictions of learning. Across three experiments, participants studied exemplars from different rock categories and later had to classify novel exemplars. Rule-based and information-based categorization was also manipulated by selecting rock sub-categories for which the optimal strategy was the one that aligned with the extraction of a simple rule, or the one that required integration of information that may be difficult to describe verbally. We observed consistent benefits of interleaving over blocking on rock classification, which generalized to both rule-based (Experiment 1) and information-integration learning (Experiments 1–3). However, providing feature descriptions enhanced classification accuracy only when the stated features were diagnostic of category membership, indicating that their benefits were limited to rule-based learning (Experiment 1) and did not generalize to information-integration learning (Experiments 1–3). Furthermore, our examination of participants’ metacognitive predictions demonstrated that participants were not aware of the benefits of interleaving on category learning. Additionally, providing feature descriptions led to higher predictions of categorization even when no significant benefits on actual performance were exhibited.
Lower bound on the distance $k$-domination number of a tree

A subset D of vertices of a graph G = (V, E) is said to be a distance k -dominating set of G if every vertex of V — D is at distance at most k from some vertex of D. The minimum size of a distance k-dominating set of G is called the distance k-domination number of G. We prove that for each tree T of order n with nx end-vertices, the distance k-domination number is bounded below by (n + 2k — k-n1)/(2k-fl) and we characterize the corresponding extremal trees.
ANALYZING BINOMIAL DATA IN A SPLIT-PLOT DESIGN: CLASSICAL APPROACHES OR MODERN TECHNIQUES?

Binomial data are often generated in split-plot experimental designs in agricultural, biological, and environmental research. Modeling non-normality and random effects are the two major challenges in analyzing binomial data in split-plot designs. In this study, seven statistical methods for testing whole-plot and subplot treatment effects using mixed, generalized linear, or generalized linear mixed models are compared for the size and power of the tests. This study shows that analyzing random effects properly is more important than adjusting the analysis for non-normality. Methods based on mixed and generalized linear mixed models hold Type I error rates better than generalized linear models. Whole-plot tests tend to be conservative in some cases, but these tests can be improved by removing the lower bound of zero from variance parameter estimation or by increasing the number of whole-plot replications. Mixed model methods tend to have higher power than generalized linear mixed models when the sample size is small. However, they perform equally well as the sample size becomes large.