Miracle-dz/UniFAR-FTUs huggingface dataset:
Gender and Age Differences in the Relationship between Sensation-Seeking and Sexual Risk-Taking Behavior among Adolescents

The study examined gender and age differences in the relationship between sensation seeking and sexual risk behaviors among secondary school students in Kenya. The study was conducted in Kisumu Municipality. Kisumu was chosen as it is one of the leading regions in HIV prevalence, estimated at 15%. The HIV prevalence was assumed to indicate a positive relationship between sensation seeking and high sexual risk-taking behavior. A sample size of 357 adolescents (44% males and 56% females) was drawn using a stratified sampling method from a population of 10,278 secondary school students. Descriptive statistics were used to analyze quantitative data, while the qualitative data was summarized thematically. The study's findings indicated that about half the adolescents were highly sensational seekers predisposing them to take risks. There also existed significant gender differences in the prevalence of sensation-seeking and sexual risk-taking behavior, with the male adolescents being higher risk-takers than their female counterparts. Similarities in the prevalence of sensation-seeking were also reported. However, this varied across ages and different gender. Female adolescents' sensation-seeking increased earlier in life than their male counterparts.Further, the study indicated gender differences in the adolescents' tendency to indulge in sexually risky behaviors due to their sensation-seeking.
The male-type mitochondrial genome of the freshwater mussel Potamilus streckersoni Smith, Johnson, Inoue, Doyle, & Randklev, 2019 (Bivalvia: Unionidae)

Abstract The global decline of freshwater mussels emphasizes the need to establish genetic resources to better understand their biology, including a unique mitochondrial biology known as doubly uniparental inheritance. In this study, we present the complete male-type (M-type) mitochondrial genome of the freshwater mussel, Potamilus streckersoni Smith, Johnson, Inoue, Doyle, & Randklev, 2019. The M-type mtDNA is approximately 16 kilobases and contains 22 tRNAs, two rRNAs, and 14 protein-coding genes, including a male-specific open reading frame. Read coverage revealed that M-type mtDNA was more abundant than female-type mtDNA in male gonadal tissue, with respect to a non-spawning male individual. Novel mitogenomes were resolved within previously described sex-specific monophyletic clades across the subfamily Ambleminae. The availability of high-quality nuclear and mitochondrial genomic data for P. streckersoni makes it a model for future research into the potential role of mtDNA in sex determination or sexual development in freshwater mussels.
Collisions of Neutron Stars with Primordial Black Holes as Fast Radio Bursts Engines

If primordial black holes (PBH) with masses of constitute a non-negligible fraction of galactic dark-matter halos, their existence should have observable consequences: they necessarily collide with galactic neutron stars (NS), nest in their centers, and accrete the dense matter, eventually converting them to NS-mass black holes while releasing the NS magnetic field energy. Such processes may explain the fast radio bursts (FRB) phenomenology, in particular their millisecond durations, large luminosities ∼1043 erg s−1, high rate of occurrence , as well as high brightness temperatures, polarized emission, and Faraday rotation. Longer than the dynamical timescale of the Bondi-like accretion for light PBH allows for the repeating of FRB. This explanation follows naturally from the (assumed) existence of the dark-matter PBH and requires no additional unusual phenomena, in particular no unacceptably large magnetic fields of NS. In our model, the observed rate of FRB throughout the universe follows from the presently known number of NS in the Galaxy.
Application of support vector machine in geodesy for the classification of vertical displacements

The article presents basic rules for constructing and training neural networks, called the Support Vector Machine technique. SVM networks can mainly be used for solving tasks of classification of linearly and nonlinearly separable data and regression as well as identifying signals and recognising increases. In this paper SVM networks have been used for classifying linearly separable data in order to formulate a model of displacements of points representing a monitored object. The problem of learning networks requires the use of quadratic programming in search of an optimum point of a Lagrange function with respect to optimised parameters. Estimated parameters determine the location of the hyperplane which maximises the separation margin of both classes.
COVID-19 and the ‘New Normal’ in Education: Exacerbating Existing Inequities in Education

This paper considers education responses to the COVID-19 pandemic, with specific reference to South Africa, examining how inequality has been exacerbated as a result of the pandemic. It outlines how education policy choices are shaped and how the (mis)use of evidence highlights the lack of meaningful and robust involvement by key education stakeholders and social science specialists, particularly from the critical tradition. COVID-19 has intensified and sharpened social, political and economic fragilities and inequities globally, forcing governments to (re)think responses to social problems and disruptions. This paper underscores three dimensions of inequity in education as a result of the pandemic: equitable teaching and learning during the lockdown and school closures; inequities that may result from the (re)opening of schools in the ‘new normal’; and the lack of attention to psychosocial support and professional development. The paper argues that while this pandemic may be new, it has exacerbated existing inequities in education provision, intensified by the COVID-19 disaster management and education policy. The paper argues for a progressive approach to education transformation in response to this pandemic and future crises and disruptions.
Power and Narcists – Ideal Types of States Based on Their Sources of National Power, Extraction Capability and Foreign Policy Behaviour

This paper aims at problematizing this distinction between status quo and revisionist/imperialist states by creating a typology of four kind of states: imperialist, status quo, young and old narcist state. The text will proceed in three sections that: 1) problematises the contemporary realist theorising; 2) reconstructs Morgenthau’s notions of sources of national and political power, ideal types of foreign policy and the character of political community and its interest; 3) presents the four ideal types of states. This typology, based on analyticist metatheory and deeply inspired by Hans Morgenthau’s thought, aims at solving problems with neorealist, and neoclassical realist theorising. Based on such non-positivist metatheory, and thus closer to the classical realist roots, it omits the offensive/defensive neorealist assumption about states motivation. By explicitly combining the three historically bound qualities of states –their sources of national power, extraction capability and foreign policy behaviour it transcends the problems with weak causal linkages between state level variables present in neoclassical realism. Hence, it exemplifies the approach to general theory-building that is practically viable for explicitly exerting normative judgement, also from the perspective non great power state actors – the consistent weakness of mainstream, contemporary realist theorising.
Steady inviscid transonic flows over planar airfoils: A search for a simplified procedure

A finite difference procedure based upon a system of unsteady equations in proper conservation form with either exact or small disturbance steady terms is used to calculate the steady flows over several classes of airfoils. The airfoil condition is fulfilled on a slab whose upstream extremity is a semi-circle overlaying the airfoil leading edge circle. The limitations of the small disturbance equations are demonstrated in an extreme example of a blunt-nosed, aft-cambered airfoil. The necessity of using the equations in proper conservation form to capture the shock properly is stressed. Ability of the steady relaxation procedures to capture the shock is briefly examined.
Long non-coding RNA ncRuPAR regulates gastric cancer cell proliferation and apoptosis via phosphoinositide 3-kinase/protein kinase B signaling

Objective: To determine the effect and mechanism of the long non-coding RNA (lncRNA) ncRuPAR (non-protein coding RNA, upstream of coagulation factor II thrombin receptor [F2R]/protease-activated receptor-1 [PAR-1]) in human gastric cancer. Methods: HGC-27-ncRuPAR overexpression and MGC-803-ncRuPAR-RNAi knockdown gastric cancer cell lines were established. We assessed the effect of ncRuPAR on cell proliferation, apoptosis, migration, and invasion using Cell Counting Kit 8, flow cytometry, scratch and transwell assays, respectively. Differentially expressed genes in HGC-27-ncRuPAR overexpression and HGC-27-empty vector cell lines were identified using Affymetrix GeneChip microarray analysis. Ingenuity Pathway Analysis (IPA) of the microarray results was subsequently conducted to identify ncRuPAR-enriched pathways, followed by validation using real time-quantitative PCR (RT-qPCR). As one of the top enriched pathways, phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway was further examined by western blotting to determine its role in ncRuPAR-mediated regulation of gastric cancer pathogenesis. Results: ncRuPAR inhibited human gastric cancer cell proliferation and induced G1/S phase arrest and apoptosis, but did not affect migration or invasion in vitro. Overexpression of ncRuPAR in vitro was found to inhibit its known target PAR-1, as well as PI3K/Akt signaling. The downstream targets of PI3K/Akt, cyclin D1 was downregulated, but there was no change in expression level of B-cell lymphoma 2 (Bcl-2). Conclusions: We showed that lncRNA-ncRuPAR could inhibit tumor cell proliferation and promote apoptosis of human gastric cancer cells, potentially by inhibiting PAR-1, PI3K/Akt signaling, and cyclin D1. The results suggest a potential role for lncRNAs as key regulatory hubs in GC progression.
Fractal Dimension as Robust Estimate of Low Carbon Steels Hardness

Application of computational methods in engineering and science constantly increases, which is also visible in sector of material science, often with promising results. In following paper, authors would like to propose fractal dimension, a mathematical method of quantifying self-similarity and complexity of spatial patterns, as robust method of hardness estimation of low carbon steels. A dataset of microstructure images and corresponding Vick ers hardness measurements of S235JR steel under different delivery conditions was created. Then, three different computational methods for evaluation of materials hardness based on microstructure image were tested. In this pa per those methods are called: (i) Otsu-based index, (ii) fractal dimension index and (iii) vision transformer index. The results were compared with method used in literature for similar problems. Comparison showed that fractal dimension performs better than other evaluated methods, in terms of median absolute error, which value was equal to 4.12 HV1, which is significantly lower than results achieved by Otsu-based index and vision transformer index, which were 4.49 HV1 and 5.07 HV1 respectively. Those results can be attributed to the relative robustness of frac tal dimension index, when compared to other methods. Robust estimation is preferable, due to the high amount of noise in the dataset, which is a consequence of the nature of used material.
Measure theory and fine properties of functions

GENERAL MEASURE THEORY Measures and Measurable Functions Lusin's and Egoroff's Theorems Integrals and Limit Theorems Product Measures, Fubini's Theorem, Lebesgue Measure Covering Theorems Differentiation of Radon Measures Lebesgue Points Approximate continuity Riesz Representation Theorem Weak Convergence and Compactness for Radon Measures HAUSDORFF MEASURE Definitions and Elementary Properties Hausdorff Dimension Isodiametric Inequality Densities Hausdorff Measure and Elementary Properties of Functions AREA AND COAREA FORMULAS Lipschitz Functions, Rademacher's Theorem Linear Maps and Jacobians The Area Formula The Coarea Formula SOBOLEV FUNCTIONS. Definitions And Elementary Properties. Approximation Traces. Extensions. Sobolev Inequalities Compactness. Capacity Quasicontinuity Precise Representations of Sobolev Functions. Differentiability on Lines BV FUNCTIONS AND SETS OF FINITE PERIMETER Definitions and Structure Theorem Approximation and Compactness Traces. Extensions. Coarea Formula for BV Functions. Isoperimetric Inequalities. The Reduced Boundary The Measure Theoretic Boundary Gauss-Green Theorem. Pointwise Properties of BV Functions Essential Variation on Lines A Criterion for Finite Perimeter. DIFFERENTIABILITY AND APPROXIMATION BY C1 FUNCTIONS. Lp Differentiability a.e. Approximate Differentiability Differentiability A.E. for W1,P (P > N). Convex Functions Second Derivatives a.e. for convex functions Whitney's Extension Theorem Approximation by C1 Functions NOTATION REFERENCES
Analysis of the Visual to Verbal Mathematical Representation Process for Junior High School Students in Solving HOTS Questions in terms of Adversity Quotient

Representation is a tool to solve a problem in the form of interpretation of what students think of a problem in the form of visual, verbal, and algebraic or symbolic representations. Solving non-routine problems in mathematics learning requires high order thinking skills (HOTS). Solving student problems, both routine and non-routine problems can be influenced by the ability of students to process existing problems into a challenge that must be passed, which is called Adversity Quotient. The purpose of this study was to describe the process of visual to verbal mathematical representation of junior high school students in solving HOTS questions in terms of the adversity quotient. The research uses a qualitative approach, the type of research used in this research is descriptive qualitative research. The data obtained in the form of written test results data, questionnaire results data and interview data will be submitted in written or oral form in narrative form. The instruments used are in the form of tests and questionnaires. The result show that the subject representation process with the adversity quotient level for the climber category has met the representation process indicators well in the three HOTS questions that were worked on. Subjects with the adversity quotient level in the camper category have not been able to meet the indicators of the representation process in the HOTS problem of creating.
Description of CRESST-II data

In CRESST-III, 10 cryogenic detector modules optimized for low energy thresholds were operated for almost two years (May 2016 - February 2018). Together with this document we are publishing data from the best performing detector module which has a nuclear recoil threshold of 30.1eV. With this data-set we were able to set limits on the cross-section for spin-dependent and spin-independent elastic scattering of dark matter particles off nuclei at dark matter masses down to 160MeV/c$^2$. We publish the energies of all events after data selection as well as of all events within the acceptance region for dark-matter searches. In this document we describe how to use these data sets.
How international rents moderate business cycles’ relationship to high homicide rates

ABSTRACT I explore the relationships between macroeconomic conditions and how the forms of integration into the global economy affect homicide rates in 21 high-violence countries from 2000 to 2018. The analysis focuses on countries integrated into the global economy by accruing international economic rents. I use data from 2000 to 2018 to analyse how resource rents and remittances moderated the relationship between business cycles and high homicide rates. Moreover, I also evaluate how socioeconomic conditions mediate the above relationship. The results indicate that natural resource rents conditioned a procyclical relationship between business cycles and homicide rates. Contrastingly, remittances conditioned a countercyclical relationship between business cycles and homicide rates. The findings contribute to the rich and growing economic criminology and international political economy literature investigating how international rents condition subnational violence.
Is citizen science queering science? An exploration of the personal dimensions of engaging LGBTQ+ citizen science volunteers

ABSTRACT Citizen science, a field and practice that commonly involves ‘non experts’ engaging in scientific activities, is an avenue of science engagement that commonly results in increased scientific knowledge, literacy, and skills for the volunteers that participate. In recent years there have been increasing efforts to better understand the myriad outcomes for participants including how personal dimensions of these citizen science volunteers, such as their identities, background, cultures, and experiences, contribute to their relationships with citizen science as well as the broader field of STEM. While previous studies have acknowledged the lack of demographic diversity in terms of gender, race/ethnicity, education, and socioeconomic status, there remains little record of the sexual orientation and/or gender identity of citizen science volunteers. The aim of this study was to understand the personal dimensions of engaging LGBTQ+ volunteers in citizen science including the relationships between their queer and science identities. Based on the perspectives and experiences of 14 LGBTQ+ citizen science volunteers as shared in semi-structured interviews, this article suggests that citizen science practitioners have the potential to reduce barriers faced by queer citizen science volunteers by taking actions and enacting strategies that welcome, respect, involve, and retain LGBTQ+ participants.
Establishment of a Coal Mine Roadway Model Based on Point Cloud Feature Matching

A coal mine roadway is a longitudinally limited space with curves and branches, low illumination and high humidity, a large amount of dust, and an unstructured terrain environment. Traditional ICP algorithms have the defects of slow convergence speed and it is easy to fall into local optimums. While the NDT algorithm in the NDT + ICP algorithm has high registration efficiency, poor stability, and low registration accuracy, which are not suitable for point clouds with noise and a large amount of data. By calculating the FPFH value, the detailed description of the point cloud will be greatly increased to increase the robustness and accuracy Therefore, a feature registration method based on the FPFH + ICP algorithm is proposed to reduce the modeling error of excavation roadways and meet the requirements of intelligent excavation. First, outliers caused by dust are treated by the Euclidean clustering point cloud segmentation method, and then the calculation of the normal vector in the FPFH feature descriptor is optimized based on extracting key points from the roadway structure. The surface normal vector of each key point and its neighborhood point is estimated according to the measured point and its neighborhood point. The initial coordinate transformation matrix of a point cloud of an excavated roadway is obtained by the SAC-IA algorithm and transferred to the ICP algorithm. Finally, KD-tree is introduced into the ICP algorithm to accelerate the search speed of corresponding point pairs, and the Gauss–Newton method is used to optimize the solution of the nonlinear objective function of the algorithm to complete accurate registration of point clouds in an excavation roadway.
Physicochemical Studies of Benzocaine Bearing Heterocycles as Potential Antioxidant Agents

Abstract Series of new thirteen annulated heterocyclic were prepared and screened for their antioxidant activities. The ethyl-4(2-cyanoacetamido)benzoate as a multifunctional component which possess both electrophilic and nucleophilic centers that were utilized in organic synthesis of different candidates. These new compounds studied as antioxidants at different concentrations based on DPPH and ABTS assays using ascorbic acid as a standard antioxidant. The most potent compound was 5 that recorded as the best antioxidant compound with IC50 equal 0.006 mg/ml for DPPH results. While for ABTS study, compound 4 anticipated the best result with IC50 equal 27.46 µM. Different reactive and thermodynamic descriptors were calculated as a preliminary step for a comparative thermodynamic study for antioxidant property. The results clarified that the potent compounds showed dependence on SET–PT mechanism than HAT or SPLET mechanism. These mechanisms depended on different parameters as proton affinity and electron transfer energy that were studied. SET–PT mechanism was dependent on two descriptors: IP and BDE which were studied and observed that were less-valued in site A for two potent compounds 4 and 5. Graphical Abstract
Compressing and interpreting word embeddings with latent space regularization and interactive semantics probing

Word embedding, a high-dimensional (HD) numerical representation of words generated by machine learning models, has been used for different natural language processing tasks, for example, translation between two languages. Recently, there has been an increasing trend of transforming the HD embeddings into a latent space (e.g. via autoencoders) for further tasks, exploiting various merits the latent representations could bring. To preserve the embeddings’ quality, these works often map the embeddings into an even higher-dimensional latent space, making the already complicated embeddings even less interpretable and consuming more storage space. In this work, we borrow the idea of β VAE to regularize the HD latent space. Our regularization implicitly condenses information from the HD latent space into a much lower-dimensional space, thus compressing the embeddings. We also show that each dimension of our regularized latent space is more semantically salient, and validate our assertion by interactively probing the encoding-level of user-proposed semantics in the dimensions. To the end, we design a visual analytics system to monitor the regularization process, explore the HD latent space, and interpret latent dimensions’ semantics. We validate the effectiveness of our embedding regularization and interpretation approach through both quantitative and qualitative evaluations.