Miracle-dz/UniFAR-FTUs huggingface dataset:
Strong field single ionization of atoms and small molecules

Wepresent the hybrid anti-symmetrized coupled channelsmethod for the calculation of fully differential photo-electron spectra ofmulti-electron atoms and smallmolecules interactingwith strong laserfields. Themethod unites quantum chemical few-body electronic structure with strongfield dynamics by solving the time dependent Schrödinger equation in a fully anti-symmetrized basis composed ofmulti-electron states fromquantumchemistry and a one-electron numerical basis. Photoelectron spectra are obtained via the time dependent surface flux (tSURFF)method. Performance and accuracy of the approach are demonstrated for spectra from the helium and beryllium atoms and the hydrogenmolecule in linearly polarized laserfields at wavelengths from21 to 400 nm.At longwavelengths, helium and the hydrogenmolecule at equilibrium inter-nuclear distance can be approximated as single channel systemswhereas berylliumneeds amulti-channel description.
Family Socio-Economic Status, School Location and Students’ Eco-Friendly Knowledge, Attitude and Practices in Nigeria

The school system, regardless of the level of operation, is generally accepted as a major agent of education. It provides avenues for interaction between students and teachers on subject matters. However, the location of the school determines many students’ knowledge, attitude and practices. Also, there is an increasing awareness of the importance of the parents’ role in the progress and educational development of their children. Family background as an important and weighty factor in determining the academic performance attained by the student needs to be investigated. This study adopted a pre-test-post-test control group quasi-experimental design. Intact class of Junior Secondary School II Social Studies students in each of the six schools in Oyo state were randomly assigned to the experimental and control groups. Three validated instruments were used in this study, and they are Environmental Education Knowledge Test (EEKT), Environmental Education Attitude Scale (EEAS) and Environmental Education Practice Questionnaire (EEPQ). The data were analyzed using Analysis of Covariance (ANCOVA) with the pretest scores used as covariates. All the null hypotheses were tested at P < . 05 level of significance. The study showed a significant two-way interaction effect of family socio-economic status and school location on students’ eco-friendly knowledge, attitude and practices. It was recommended that schools should be kept safe and parents should develop more streams of income, as a single income source has become a great economic challenge in Nigeria.
Effective Low-Level Laser Therapy Including Laser Acupuncture Treatment Conditions for Non-Specific Chronic Low Back Pain: Systematic Review and Meta-Analysis

Low-level laser therapy including laser acupuncture has been widely used for non-specific chronic low back pain in primary Korean medical clinics. However, there is no critically appraised data regarding which treatment conditions are most effective. A systematic review and meta-analysis was conducted to determine effective treatment conditions using 12 databases (PubMed, Ovid, CENTRAL, KoreaMed, KMBASE, KISS, NDSL, KISTI, OASIS, CNKI, CiNII, and J-STAGE). There were 1,019 studies retrieved and 13 studies included in this review. It was determined that when the power output was ≥ 50 mW, the beam size was increased to ≥ 1 cm2, the energy dose was increased to ≥ 4 J per point, the treatment interval was increased to ≥ 3 times a week, and the number of treatment sessions was increased to ≥ 10 treatments, these conditions appeared to increased treatment effectiveness.
Learning reduced‐order dynamics for parametrized shallow water equations from data

This paper discusses a non‐intrusive data‐driven model order reduction method that learns low‐dimensional dynamical models for a parametrized shallow water equation. We consider the shallow water equation in non‐traditional form (NTSWE). We focus on learning low‐dimensional models in a non‐intrusive way. That means, we assume not to have access to a discretized form of the NTSWE in any form. Instead, we have snapshots that can be obtained using a black‐box solver. Consequently, we aim at learning reduced‐order models only from the snapshots. Precisely, a reduced‐order model is learnt by solving an appropriate least‐squares optimization problem in a low‐dimensional subspace. Furthermore, we discuss computational challenges that particularly arise from the optimization problem being ill‐conditioned. Moreover, we extend the non‐intrusive model order reduction framework to a parametric case, where we make use of the parameter dependency at the level of the partial differential equation. We illustrate the efficiency of the proposed non‐intrusive method to construct reduced‐order models for NTSWE and compare it with an intrusive method (proper orthogonal decomposition). We furthermore discuss the predictive capabilities of both models outside the range of the training data.
Panoramic Image-Based Aerial Localization using Synthetic Data via Photogrammetric Reconstruction

To successfully adhere to flight plans, aerial vehicles must keep track of their location in 3D space, which is usually reliant on external references such as GNSS which are susceptible to interference. To develop self-reliant onboard positional localization, a workflow using 360-degree panoramic images in an image-based localization system using a Deep Convolutional Neural Network is proposed. 360-degree panoramic images have the advantage that they take into account visual information from all angles. Model performance is also enhanced by generating synthetic data from a 3D model of the region of interest created via photogrammetry techniques. The performances of different training configurations are compared, and the configuration with mixed real and synthetic data exhibits the highest performance, an approximately 10 to 15 percent improvement over using solely real data. Additional image augmentations also further reduce the localization error by 8 to 15 percent.
Can the Dunning-Kruger effect occur in the motor performance domain?

ABSTRACT The Dunning-Kruger effect is commonly understood as the tendency of relatively poor performers to grossly overestimate their ability and performance. This effect has been observed in a number of domains for which competence is wholly dependent on domain specific knowledge (e.g., the academic domain; the medical domain). However, it is claimed that the motor performance domain is not susceptible to the Dunning-Kruger effect because competence in this domain is dependent on factors other than knowledge (e.g., physical skill). The present study aims to test this claim. Eighty-three male participants performed one trial of the hand-grip strength task using their dominant hand. They also estimated their relative ability on the task, their relative performance on the task, and their score on the task. Participants were split into quartiles based on their actual task score. For each quartile, the mean estimated ability percentile and the mean estimated performance percentile were compared to the mean actual task score percentile. Also, mean estimated task score and mean actual task score were compared across quartiles. Consistent with the typical Dunning-Kruger effect, it was found that the worst performers were the most miscalibrated and significantly overestimated themselves, whereas the best performers significantly underestimated themselves. These findings indicate that the Dunning-Kruger effect can occur in the motor performance domain. They also cast doubt on the adequacy of the “metacognitive deficit” explanation, suggesting instead that, in the motor performance domain, motivational biases and defenses play a key role in the Dunning-Kruger effect.
Phase field modelling of grain growth with particle pinning and solute drag

Second phase particles and solute atoms have been used as an important constituent in the design of materials and processes due to their ability to restrain the motion of grain boundaries. The drag effect occurs on a scale comparable to the particle diameter and interface thickness. However, to simulate grain growth with numerical efficiency one requires a model that captures the drag pressure on the interfaces but does not resolve the particles or solute segregation spike. In this work, a multi-scale modelling scheme is proposed to simulate grain growth with particle pinning and solute drag. The interaction of a grain boundary with an ensemble of particles is simulated to obtain the pinning pressure. A phase field model is then developed that incorporates the drag pressure in the meso-scale and simulates grain growth. The accuracy of the model is confirmed in comparison with analytical expressions. The application of the model is then presented for grain growth in twoand three-dimensional systems under the influence of particle pinning. Measuring the curvature of the grain boundary network reveals that in the completely pinned structure, the average driving pressure is not equal to but lower than the pinning pressure. The results of the nano-scale simulations for pinning pressure is combined with the results from the meso-scale to produce a limiting grain size that coincides with the experiments. This curvature analysis provides a kinetic model that describes the evolution of the structure more accurately than that of the mean field theories. The proposed phase field formulation is also applied to simulate grain growth in the presence of solute drag. The grain growth kinetics follows a phenomenological relationship that is described using a power law, with a time exponent in the range of 0.35 to 0.50. The deviation from ideal grain growth, associated with a time exponent lower than 0.5, and its correlation with the solute drag parameters is investigated.
DFT STUDY ON HYDROGENATION REACTION OF ACETALDEHYDE TO ETHANOL IN GAS AND WATER PHASE

Numerical investigation of hydrogenation reaction of acetaldehyde to ethyl alcohol has been done in two phases, i.e. gaseous and aqueous phase separately using Gaussian 09 software package. For aqueous phase calculations, solvation approach has been taken and applied SMD model with water as solvent. Geometries were optimized at B3LYP functional of density functional theory (DFT) with the basis set of 6-31g(d) in both the phases. An imaginary frequency in frequency calculation result affirms the transition state. For getting an optimized structures of reactant and product, intrinsic reaction coordinate (IRC) calculation is carried out on the transition state structure at the same level of theory, in both phases. IRC connects the both minima in both forward and backward directions linking with transition state structure. Single point energy (SPE) has been calculated to get more accurate values of the optimized structures of reactant, product and transition state in both phases, i.e., gas and water at CCSD/6-311+g(3df,2p) theory.
Renal and Red Marrow Dosimetry in Peptide Receptor Radionuclide Therapy: 20 Years of History and Ahead

The development of dosimetry and studies in peptide receptor radionuclide therapy (PRRT) over the past two decades are reviewed. Differences in kidney and bone marrow toxicity reported between 90Y, 177Lu and external beam radiotherapy (EBRT) are discussed with regard to the physical properties of these beta emitter radionuclides. The impact of these properties on the response to small and large tumors is also considered. Capacities of the imaging modalities to assess the dosimetry to target tissues are evaluated. Studies published in the past two years that confirm a red marrow uptake in 177Lu-DOTATATE therapy, as already observed 20 years ago in 86Y-DOTATOC PET studies, are analyzed in light of the recent developments in the transferrin transport mechanism. The review enlightens the importance (i) of using state-of-the-art imaging modalities, (ii) of individualizing the activity to be injected with regard to the huge tissue uptake variability observed between patients, (iii) of challenging the currently used but inappropriate blood-based red marrow dosimetry and (iv) of considering individual tandem therapy. Last, a smart individually optimized tandem therapy taking benefit of the bi-orthogonal toxicity-response pattern of 177Lu-DOTATATE and of 90Y-DOTATOC is proposed.
Design Improvement for Complex Systems with Uncertainty

The uncertainty of the engineering system increases with its complexity, therefore, the tolerance to the uncertainty becomes important. Even under large variations of design parameters, the system performance should achieve the design goal in the design phase. Therefore, engineers are interested in how to turn a bad design into a good one with the least effort in the presence of uncertainty. To improve a bad design, we classify design parameters into key parameters and non-key parameters based on engineering knowledge, and then seek the maximum solution hyper-box which already includes non-key parameters of this bad design. The solution hyper-box on which all design points are good, that is, they achieve the design goal, provides target intervals for each parameter. The bad design can be turned into a good one by only moving its key parameters into their target intervals. In this paper, the PSO-Divide-Best method is proposed to seek the maximum solution hyper-box which is in compliance with the constraints. This proposed approach has a considerably high possibility to find the globally maximum solution hyper-box that satisfies the constraints and can be used in complex systems with black-box performance functions. Finally, case studies show that the proposed approach outperforms the EPCP and IA-CES methods in the literature.
Defence responses of grapevine cultivars to powdery mildew: Ontogenic resistance versus genetic resistance

The most sustainable management of resistant varieties involves understanding which defence mechanisms the plant uses according to its resistance genes and stage of development and how effective these mechanisms are. Three grapevine varieties were compared for their susceptibility versus resistance to powdery mil-dew: Vitis vinifera ‘Cabernet Sauvignon’ (CS) and two hybrids, ‘Artaban’ and ‘Prior’. Four different leaf ages were collected from 2- year-old grafted grapevines planted in pot or in vineyard, and several variables were assessed for each leaf: (a) morphological and physiological indicators, (b) pathogenicity traits: spore germination, infection efﬁciency, mycelial growth and sporulation, and (c) gene expression using a high-throughput quantitative reverse transcription PCR method to inform about plant defence status and functioning of primary metabolism. A significant decrease in germination and sporulation with increasing leaf age were observed for the three varieties: Prior showed a susceptibility similar to that of CS, whereas Artaban was fully resistant with no sporulation. Genes highlighted as markers of the variety were involved in defence ( VvPR3 , VvPR4 overexpressed in Artaban, VvPR4bis , VvAlli2 in Prior) or in primary metabolism (repression of VvCitS in Artaban, VvCHI in Prior, overexpression of VvCAD2 , VvGST3 in Prior). After inoculation, more defence genes, especially PR proteins, were overexpressed in the oldest leaves as potential com - ponents of ontogenic resistance. PR proteins accounted for 25% of total disease variation. Phenylpropanoid and ethylene pathways were leaf age-dependent. The statistical method used highlighted the contributions of the genotypic expression involved in genetic (cultivar) and ontogenic (leaf age) resistances and of the metabolic pathways to the disease.
Young People’s Views on Food Hygiene and Food Safety: A Multicentre Qualitative Study

Foodborne diseases are a global burden, are preventable, and young people are a key population for behaviour change as they gain autonomy. This study aimed to explore young people’s needs across several European countries in relation to learning about and implementing food hygiene and food safety. Qualitative focus groups and interviews were conducted in rural and city regions across England, France, Hungary and Portugal. Data were collected to attain data saturation, transcribed, thematically analysed, and mapped to the Theoretical Domains Framework. Twenty-five out of 84 schools approached (29.8%) participated, with data collected from 156 11–18-year-old students. Students had good knowledge of personal hygiene but did not always follow hygiene rules due to forgetfulness, lack of facilities or lack of concern for consequences. Students had limited understanding of foodborne microbes, underestimated the risks and consequences of foodborne illness and perceived the “home” environment as the safest. Young people preferred interactive educational methods. Addressing gaps in young people’s food safety knowledge is essential to improve their lack of concern towards foodborne illness and motivate them to follow food hygiene and safety behaviours consistently. Findings have been used to develop educational resources to address gaps in knowledge, skills, attitudes and beliefs.
Sequential Multi-objective Genetic Algorithm

Many of the real-world issues have multiple conflicting objectives that the optimization between contradictory objectives is very difficult. In recent years, the Multi-objective Evolutionary Algorithms (MOEAs) have shown great performance to optimize such problems. So, the development of MOEAs will always lead to the advancement of science. The Non-dominated Sorting Genetic Algorithm II (NSGAII) is considered as one of the most used evolutionary algorithms, and many MOEAs have emerged to resolve NSGAII problems, such as the Sequential Multi-Objective Algorithm (SEQ-MOGA). SEQ-MOGA presents a new survival selection that arranges individuals systematically, and the chromosomes can cover the entire Pareto Front region. In this study, the Archive Sequential Multi-Objective Algorithm (ASMOGA) is proposed to develop and improve SEQ-MOGA. ASMOGA uses the archive technique to save the history of the search procedure, so that the maintenance of the diversity in the decision space is satisfied adequately. To demonstrate the performance of ASMOGA, it is used and compared with several state-of-the-art MOEAs for optimizing benchmark functions and designing the I-Beam problem. The optimization results are evaluated by Performance Metrics such as hypervolume, Generational Distance, Spacing, and the t-test (a statistical test); based on the results, the superiority of the proposed algorithm is identified clearly.
Halogen and solvent effects on the conformational, vibrational and electronic properties of 1,4-diformylpiperazine: A combined experimental and DFT study

The molecular structure and properties of 1,4-diformylpiperazine (1,4-dfp, C6H10N2O2) were investigated by Fourier transform infrared (FT-IR) spectroscopy, Raman spectroscopy and density functional theory (DFT). The Becke-3-Lee–Yang–Parr (B3LYP) functional was used with the 6-31++G(d,p) basis set. Total energy distribution (TED) analysis of normal modes was performed to identify characteristic frequencies by the scaled quantum mechanical (SQM) method. Halogeno-analogs of 1,4-dfp were studied to understand the halogen effect. Computations were focused on five conformational isomers of the compounds in the gas phase and in solutions. The computed and experimental frequencies of the C=O stretching vibration of 1,4-dfp were correlated with the empirical solvent parameters such as the Kirkwood–Bauer–Magat (KBM) equation, the solvent acceptor number (AN), Swain parameters and linear solvation energy relationships (LSER). The electronic properties of the compounds were also examined. The findings from the present work may be useful to understand systems involving the halogens and conformational changes analogous to the compounds investigated.
Social Media and Emergency Services: Information Sharing about Cases of Missing Persons in Rural Sweden

The aim of this article is to investigate the nature of information sharing in social media about missing persons by using social media data (mostly Twitter) and conventional media coverage (media archives), adopting a platial perspective to this geographical information. By focusing on the cases of three people gone missing, we report on ways in which civil society establishes relational networks through social media to collectively support local searches and share information in rural Sweden. Geographical information systems and visualization techniques underlie the methodology of this study. Findings show that the geography of information sharing in social media about a missing person is not random, revealing a globally dispersed pattern across the country. Information sharing contains more emotional than informational content, hitting a peak of spread after a person is found deceased. This finding indicates that the value of information shared by social media as a problem-solving resource might have so far been overestimated in the process of finding missing persons. In addition, tweets show indications that voluntary organizations constitute a valuable resource in rural contexts but not without impact on the existing networks of stakeholders delivering emergency services.
A Model for Nonlinear Electrokinetics in Electric Field Guided Assembly of Colloids

A Model for Nonlinear Electrokinetics in Electric Field Guided Assembly of Colloids. (December 2009) James G. Steuber, B.S., Arkansas Tech University; M.EN. , Texas A&M University Chair of Advisory Committee: Dr. J.N. Reddy Electric field guided assembly of colloids is a new area of research in colloidal science where sub-micrometer particles, or colloids, are assembled using patterned electrodes. The design of these devices is often limited by an inability to characterize accurately forces and fluxes with linearized electrokinetic theory. The research presented in this dissertation describes an application of the finite element method to the nonlinear electrokinetic equations. The finite element model thus developed is then used to describe the nonlinear electrophoretic mobility of a dilute colloidal dispersion, investigate hydrodynamic and electric particle-particle interactions, and characterize particle-surface interactions. The effect of Stern layer conduction on the electrophoretic mobility and dielectric response is included using the generalized dynamic Stern layer model. The electrokinetic force is calculated using the Maxwell stress tensor method rather than the effective dipole method as it is more consistent with nonlinear electrokinetic theory. Significant results of this dissertation demonstrate the effect of nonlinear electrokinetic phenomena and extend the present electrokinetic theory. The calculation
STEM-Focused Career Courses and College Pipeline for Students with Learning Disabilities

Recent educational policies in the United States have fostered the growth of science, technology, engineering, and mathematics (STEM) career-focused courses to support high school students’ persistence into these fields in college and beyond. As one key example, federal legislation has embedded new types of “applied STEM” (AS) courses into the career and technical education curriculum (CTE), which can help students persist in STEM through high school and college. Yet, little is known about the link between AS-CTE coursetaking and college STEM persistence for students with learning disabilities (LDs). Using a nationally representative data set, we found no evidence that earning more units of AS-CTE in high school influenced college enrollment patterns or major selection in non-AS STEM fields for students with LDs. That said, students with LDs who earned more units of AS-CTE in high school were more likely to seriously consider and ultimately declare AS-related STEM majors in college.