Miracle-dz/UniFAR-FTUs huggingface dataset:
Algorithmic autobiographies and fictions: A digital method

In this article, we outline an original, creative method for capturing the multifaceted ways in which digital technologies shape social life. We outline a framework for engaging participants in creative writing and drawing techniques to support ‘meeting and greeting’ their ‘algorithmic selves’. Algorithmic selves offer datafied reflections of individuals’ social media use, represented through platform approximated advertising categories. These categories include identities, such as ‘female’ or ‘male’, and marketing interests as ‘dog lovers’, ‘first time buyers’ or ‘feminists’. Our method builds on Les Back’s calls for ‘a more artful form of sociology’ that is able to think with technology. By using algorithmic selves to mobilise creative enquiry in this way, we argue that researchers can better discern how technology users make sense of their data, the ways in which identity can be co-constructed by social media platforms, and how our interactions with technology ultimately shape social lives in meaningful and highly affective ways. Our method offers a craft-based framework for understanding imaginations, associations and connections with data profiling, and making these understandings available for participant reflection and researcher analysis. This method can also support research participants in taking creative ownership and building agency around their interactions with social media platforms.
QSO heavy element absorption systems and the nature of the metagalactic ionizing flux at high redshift

Given that the observed QSOs cannot account for the intensity of the metagalactic ultraviolet flux at high redshift, the possible contribution from early-type stars in young or forming galaxies is examined. Based on the observed ionization state of heavy element absorption systems in the spectra of QSOs, and using photoionization models, arguments are presented which appear to rule out the possibility that early-type stars in young or forming galaxies are dominating the metagalactic ultraviolet flux up to a redshift of at least z about 4. Specifically, the stellar contribution cannot be more than comparable to the AGN contribution, and thus it appears that unaccounted-for sources of ionizing radiation which have spectral energy distributions similar to those of AGNs must be present at high redshifts. 25 refs.
Investigating the Potential of Thin Silicon Nitride Membranes in Fiber-Based Photoacoustic Sensing

The detection of methane, a strong greenhouse gas, has increased in importance due to rising emissions, which partly originate from unreported and undetected leaks in oil and gas fields. The gas emitted by these leaks could be detected using an optical fiber-based photoacoustic sensor called PAS-WRAP. Here, we investigate the potential of silicon-based membranes as more sensitive microphones in the PAS-WRAP concept. Toward this goal, we built a setup with which the frequency response of the membranes was interrogated by an optical fiber. Multiple mounting mechanisms were tested by adapting commercial interferometry systems (OP1550, ZonaSens, Optics11 B.V.) to our case. Finally, methane detection was attempted using a silicon nitride membrane as a sensor. Our findings show a quality factor of 2.4 at 46 kHz and 33.6 at 168 kHz for a thin silicon nitride membrane. This membrane had a frequency response with a signal-to-background ratio of 1 ± 0.7 at 44 kHz when tested in a vacuum chamber with 4% methane at 0.94 bar. The signal-to-background ratio was not significant for methane detection; however, we believe that the methods and experimental procedures that we used in this work can provide a useful reference for future research into gas trace detection with optical fiber-based photoacoustic spectroscopy.
Rotor Performance and Turbulent Wake Simulations of a Scaled Helicopter Rotor in Hover Using Wall-Modeled Large-Eddy Simulations

A scaled helicopter rotor in hover is studied using wall-modeled large-eddy simulations (WMLES). Performance is evaluated for three thrust conditions at varying grid resolutions and validated with experimental measurements. Capturing the eﬀects of the laminar-turbulent transition over the blade, and the subsequent impact on blade forces, poses a signiﬁcant challenge for the equilibrium wall model. Results indicate that a mesh with around two grid points in the turbulent boundary layer predicts forces that indicate fully turbulent ﬂow over the blade. Meshes with around seven grid points in the turbulent boundary layer can capture some transitional impact on blade forces, despite not accurately predicting transition location. Further conﬁrmation of viscous force impact on rotor loads was evaluated with simulations using a blowing-suction trip to force transition and a wall-model sensor to act as a crude transition model.
Multipolar second-harmonic generation in noble metal nanoparticles

Second-harmonic generation from noble metal nanoparticles with a noncentrosymmetrical shape is theoretically investigated by using finite element method simulations. The relative weight of the dipolar and quadrupolar responses is investigated in terms of both light polarization and size dependence of the harmonic scattered intensity. It is shown that, even for small deformations as compared with purely spherical particles, the dipolar response dominates and scales as the nanoparticle surface area squared. The difference between gold and silver metal nanoparticles is also addressed.
Does a Curriculum Integration Intervention to Improve the Mathematics Achievement of Students Diminish Their Acquisition of Technical Competence? An Experimental Study in Agricultural Mechanics.

The purpose of this study was to empirically test the hypothesis that students who participated in a contextualized, mathematics-enhanced high school agricultural power and technology curriculum and aligned instructional approach would not experience significant diminishment in acquisition of technical skills related to agricultural power and technology compared with those students who participated in the traditional curriculum. This study included teachers and students from 38 high schools in the state of Oklahoma (18 experimental classrooms; 20 control classrooms). Students were enrolled in an agricultural power and technology course in the spring semester of 2004. The total number of students who participated was 447 (206 experimental; 241 control). The experimental design employed was a posttest only control group design. One-way analysis of variance (ANOVA) was used to test the study’s null hypothesis. The math-enhanced agricultural power and technology curriculum and aligned instructional approach did not significantly diminish (p > .05) students’ acquisition of technical skills as measured by the National Occupational Competency Testing Institute (NOCTI) Agriculture Mechanics examination. A one-year replication of the study described is recommended.
A Distribution-Free Multivariate Sign Test Based on Interdirections

Abstract Distribution-free tests are investigated for the one-sample multivariate location problem. Counts, called interdirections, which measure the angular distance between two observation vectors relative to the positions of the other observations, are introduced. These counts are invariant under nonsingular linear transformations and have a small-sample distribution-free property over a broad class of population models, called distributions with elliptical directions, which includes all elliptically symmetric populations and many skewed populations. A sign test based on interdirections is described, including, as special cases, the two-sided univariate sign test and Blumen's bivariate sign test. The statistic is shown to have a limiting χ2 p null distribution and, because it is based on interdirections, it is also seen to be invariant and to have a small-sample distribution-free property. Pitman asymptotic relative efficiencies and a Monte Carlo study show the test to perform well compared with Hotell.
Edge Computing Enabled Energy-Efficient Multi-UAV Cooperative Target Search

Multiple unmanned aerial vehicles (UAVs) cooperative search have been widely adopted for surveillance and search-related applications. For a certain search area, UAVs may need to search it repeatedly to obtain a high-confidence result about the target distribution in the search area. However, the short battery life and moderate computational capability restrict UAVs to repeatedly execute the computation-intensive and energy-consuming search tasks. To address the issue, in this paper, we utilize edge computing to develop a continual and cooperative UAV search mechanism. Specifically, we first establish an edge computing enabled multi-UAV cooperative search framework, in which the mobility model of UAV, search task computing and offloading models are presented. An uncertainty minimization problem is then formulated, aiming to obtain a high-efficiency and high-confidence search result at the unpredictable uncertainty in search area. Considering that round-trip energy consumption, offloading decision-making, and trajectory planning may contribute to the reduction in uncertainty, we propose an uncertainty minimization-based cooperative target search (UMCTS) strategy. Finally, extensive simulation results validate that UMCTS can outperform the existing strategies and achieve at least 89% performance gain on average uncertainty. Based on the results, we also present a comprehensive analysis and discussion on how different parameters affect the search performance.
New‐Generation Anion‐Pillared Metal–Organic Frameworks with Customized Cages for Highly Efficient CO2 Capture

The rational design of porous materials for CO2 capture under realistic process conditions is highly desirable. However, trade‐offs exist among a nanopore's capacity, selectivity, adsorption heat, and stability. In this study, a new generation of anion‐pillared metal‐organic frameworks (MOFs) are reported with customizable cages for benchmark CO2 capture from flue gas. The optimally designed TIFSIX‐Cu‐TPA exhibits a high CO2 capacity, excellent CO2/N2 selectivity, high thermal stability, and chemical stability in acid solution and acidic atmosphere, as well as modest adsorption heat for facile regeneration. Additionally, the practical separation performance of the synthesized MOFs is demonstrated by breakthrough experiments under various process conditions. A highly selective separation is achieved at 298–348 K with the impressive CO2 capacity of 2.1–1.4 mmol g−1. Importantly, the outstanding performance is sustained under high humidity and over ten repeat process cycles. The molecular mechanism of MOF's CO2 adsorption is further investigated in situ by CO2 dosed single crystal structure and theoretical calculations, highlighting two separate binding sites for CO2 in small and large cages featured with high CO2 selectivity and loading, respectively. The simultaneous adsorption of CO2 inside these two types of interconnected cages accounts for the high performance of these newly designed anionic pillar‐caged MOFs.
Bayesian Inference for Multivariate Survival Data with a Cure Fraction

We develop Bayesian methods for right censored multivariate failure time data for populations with a cure fraction. We propose a new model, called the multivariate cure rate model, and provide a natural motivation and interpretation of it. To create the correlation structure between the failure times, we introduce a frailty term, which is assumed to have a positive stable distribution. The resulting correlation structure induced by the frailty term is quite appealing and leads to a nice characterization of the association between the failure times. Several novel properties of the model are derived. First, conditional on the frailty term, it is shown that the model has a proportional hazards structure with the covariates depending naturally on the cure rate. Second, we establish mathematical relationships between the marginal survivor functions of the multivariate cure rate model and the more standard mixture model for modelling cure rates. With the introduction of latent variables, we show that the new model is computationally appealing, and novel computational Markov chain Monte Carlo (MCMC) methods are developed to sample from the posterior distribution of the parameters. Specifically, we propose a modified version of the collapsed Gibbs technique (J. S. Liu, 1994, J. Amer. Statist. Assoc.89, 958? 966) to sample from the posterior distribution. This development will lead to an efficient Gibbs sampling procedure, which would otherwise be extremely difficult. We characterize the propriety of the joint posterior distribution of the parameters using a class of noninformative improper priors. A real dataset from a melanoma clinical trial is presented to illustrate the methodology.
Effects of Curvature on Flexible Bragg Grating in Off-Axis Core: Theory and Experiment

A high curvature flexible Bragg grating, in planar technology, is designed, fabricated and experimentally characterized by employing silica glass. The curvature sensing mechanism for slightly off-axis core is theoretically explained and experimentally demonstrated. The electromagnetic behavior of the proposed sensor is investigated through conformal mapping, modal analysis, and coupled-mode theory. The experimental measurement reveals different sensitivities to positive and negative curvatures. The reflection spectrum of the planar Bragg grating sensor and the relationship between its resonant wavelengths and the curvature is measured for a large curvature range up to $1/R = \pm \ 33\,\text{m}^{ - 1}$. The interest toward off-axis core on planar flexible platform for curvature monitoring is due to the lateral stiffness and low Young's modulus of the substrate.
Learning Spectrum-Invariance Representation for Cross-Spectral Palmprint Recognition

Palmprint recognition provides a potential solution for noninvasive personal authentication due to its excellent contactless property and user-security, and it has attracted tremendous research interest in recent years. However, most existing methods focus on intraspectral palmprint recognition, which requires gallery and probe images to be captured under similar illumination, and thus significantly limit its practical applications in open environments with variant illuminations. In this study, we present a spectrum-invariant feature learning method for cross-spectral palmprint recognition to address the problem that gallery and probe samples are captured under different spectra. First, the blockwise direction-based ordinal measure vectors are formed to represent the intrinsic information of palmprint images. Then, a unified feature projection is jointly learned to map two different spectra of palmprint images into a common feature space, in which the different spectral features have enhanced discriminative power by enlarging their variances while the intraclass features learned from different spectral images are similar. The proposed method can be easily extended to seek the unified spectrum-invariant representation of multiple spectral palmprint images, making it feasible to perform palmprint recognition crossing one spectrum to multiple spectra. Experimental results on two multispectral palmprint image databases demonstrate the promising effectiveness of the proposed method on cross-spectral palmprint recognition.
Recent experiments on the hydrodynamics of laser-produced plasmas conducted at the PALS laboratory

We present a series of experimental results, and their interpretation, connected to various aspects of the hydrodynamics of laser produced plasmas. Experiments were performed using the Prague PALS iodine laser working at 0.44 μm wavelength and irradiances up to a few 10 14 W/cm 2 . By adopting large focal spots and smoothed laser beams, the lateral energy transport and lateral expansion have been avoided. Therefore we could reach a quasi one-dimensional regime for which experimental results can be more easily and properly compared to available analytical models.
Convective Instability of Rotating Radiating Fluids

The Benard problem of a rotating radiating nongray fluid is examined analytically for both stationary and oscillatory convection. Radiation is modeled by the Milne-Eddington approximation. The time derivatives are retained in the disturbance equations and both types of instability were studied using the same approximating functions. Results presented show that, in the presence of rotation, radiation increases the zone in which overstability is the preferred mode of instability.
Análisis de sentimientos en Twitter

El análisis de sentimientos ayuda a determinar la percepción de usuarios en diferentes aspectos de la vida cotidiana, como preferencias de productos en el mercado, nivel de confianza de los usuarios en ambientes de trabajo, o preferencias políticas. La idea es predecir tendencias o preferencias basados en sentimientos. En este artículo evaluamos las técnicas más comunes usadas para este tipo de análisis, considerando técnicas de aprendizaje de máquina y aprendizaje de máquina profundo. Nuestra contribución principal se basa en una propuesta de una estrategia metodológica que abarca las fases de preprocesamiento de datos, construcción de modelos predictivos y su evaluación. De los resultados, el mejor modelo clásico fue SVM, con 78% de precisión, y 79% de métrica F1 (F1 score). Para los modelos de Deep Learning, con mejores resultados fueron los modelos clásicos. El modelo con mejor desempeño fue el de Deep Learning Long Short Term Memory (LSTM), alcanzando un 88% de precisión y 89% de métrica F1. El peor de los modelos de Deep Learning fue el CNN, con 77% de precisión como de métrica F1. Concluyendo que, el algoritmo Long Short Term Memory (LSTM) demostró ser el mejor rendimiento, alcanzando hasta un 89% de precisión.
Barriers to Breast Cancer-Screening Adherence in Vulnerable Populations

Simple Summary Breast cancer is the most prevalent cancer in the world. Early diagnosis can prevent cancer growth and therefore saving lives. Breast cancer screening through periodic mammography has been effective in decreasing mortality. However, adherence to screening does not meet the desired expectations in all population groups. The objective of this review is to identify the barriers that affect adherence to breast cancer–screening programs in an ethnically diverse group of women in order to propose public health measures to increase adherence. Although the dissemination of breast cancer–screening programs is still lacking in most of the vulnerable populations, we observed important favorable changes in those cases in which the population undergoes health education sessions, they are informed about cancer-screening programs or they seek medical attention. Therefore, implementing awareness campaigns focused on these populations should be promoted, as well as working on healthcare professional cultural competence to improve breast cancer–screening adherence worldwide. Abstract Breast cancer screening through periodic mammography has been effective in decreasing mortality and reducing the impact of this disease. However, adherence to screening does not meet the desired expectations from all populations. The main objective of this review is to explore the barriers that affect adherence to breast cancer–screening programs in vulnerable populations according to race and/or ethnicity in order to propose measures to reduce the lack of adherence. We conducted a search of publications in the PubMed Central and Scopus databases. The eligible criteria for the articles were as follows: original quantitative studies appearing in SJR- and/or JCR-indexed journals from 2016 to 2021 in English or Spanish. Most of them present common barriers, such as race/ethnicity (47%), low socioeconomic (35.3%) and educational levels (29.4%), no family history of cancer and being single (29.4%), medical mistrust and a health information gap (23.5%), lack of private health insurance (17.6%) and not having annual health checks (17.6%). The target populations with the lowest adherence were Black, Asian, Hispanic and foreign women. Implementing awareness campaigns focused on these populations should be promoted, as well as working on diversity, cultural acceptance and respect with healthcare workers, in order to improve breast cancer–screening adherence worldwide.
Effect of valence nucleons on RMS charge radii and surface thickness

The nucleonic promiscuity factor P=NpNn/(Np+Nn), where Np(Nn) is the number of valence protons (neutrons) or holes, is shown to be a useful and physically meaningful parameter in the description of RMS charge radii. The introduction of P in the radius formula R approximately=Rc+0.07P/Rc (Rc; droplet model 'closed-shell radius') reduces the chi 2/n' value by a factor of three. The empirically found mass number dependence of the P-dependent contribution to radii is in agreement with the qualitative theoretical expectation for the average strength of the isoscalar p-n interaction. A significant correlation between surface diffusity and promiscuity as well as between diffusity and radius is pointed out.
Sorghum WRKY transcription factor SbWRKY45 enhanced seed germination under drought stress in transgenic Arabidopsis

: The WRKY transcription factors (TFs) family is an important family of plant-specific TFs, playing vital roles in various abiotic and biotic stress responses. WRKY TFs are gaining considerable attention due to their significant roles in stress responses. However, their functions in sorghum ( Sorghum bicolor ) are lagging behind. In this study, a WRKY gene designated as SbWRKY45 was isolated and characterized from sorghum. SbWRKY45 , belonging to Group IIa, consists of one intron and two exons and encodes 430 amino acids. SbWRKY45 is located in chromosome 4. The cis -element prediction analysis showed that the promoter region of SbWRKY45 has several abiotic stress-associated elements. The qRT-PCR results showed that SbWRKY45 was significantly up-regulated in response to drought and cold under salt treatments, was notably changed, and was induced weakly under heat stress. SbWRKY45 exhibited a response to stress in different sorghum tissues, including leaves, stems, and roots. A tissue-specific expression pattern showed that SbWRKY45 was highly expressed in roots compared with leaves and stems, suggesting that SbWRKY45 may play an important role in roots. Overexpression of SbWRKY45 increased germination rates and promoted root growth in transgenic Arabidopsis under drought stress. Taken together, our findings indicate that SbWRKY45 may be involved in mediating the response to drought stress and play a vital role in the abiotic stress response of sorghum.
On the convergence of the Campbell–Baker–Hausdorff–Dynkin series in infinite-dimensional Banach–Lie algebras

We prove a convergence result for the Campbell–Baker–Hausdorff–Dynkin series in infinite-dimensional Banach–Lie algebras . In the existing literature, this topic has been investigated when is the Lie algebra of a finite-dimensional Lie group (see [Blanes and Casas, 2004]) or of an infinite-dimensional Banach–Lie group (see [Mérigot, 1974]). Indeed, one can obtain a suitable ODE for , which follows from the well-behaved formulas for the differential of the Exponential Map of the Lie group . The novelty of our approach is to derive this ODE in any infinite-dimensional Banach–Lie algebra, not necessarily associated to a Lie group, as a consequence of an analogous abstract ODE first obtained in the most natural algebraic setting: that of the formal power series in two commuting indeterminates over the free unital associative algebra generated by two non-commuting indeterminates .