Miracle-dz/UniFAR-FTUs huggingface dataset:
Female Education and Contraceptives Use in Nigeria

Contraceptive use is considered important for protecting women’s health and rights, influencing fertility and population growth. This study examined the impact of female education on the use of contraceptives and fertility rate in Nigeria using 2013 and 2018 cohorts of Demography and Health Survey Data. The survey covers women ages 15 to 49 years. The study shows that women’s education, income level, and cultural value are important in explaining women’s reproductive behaviour. The results reveal that female education has a positive significant effect on contraceptives use and a significant negative effect on fertility rate. The contraceptives use and fertility models show that the effects become stronger with an increase in the level of education. Notably, the study shows no significant difference in the behavioural pattern of the factors that influenced contraceptive use and fertility rate in the 2013 and 2018 cohorts of demography and health survey data. The study concludes that female education is vital in encouraging the use of contraceptives and controlling the fertility rate. Hence, the government should invest more in women education to increase women's use of contraceptives, control fertility, and population growth, protect women's health and stimulate sustainable economic development.
Application of Data Mining in the Forecasting of Railway Passenger Flow

This paper through studying the theory of data warehouse and data mining, applies these technologies to deal with the large number data in the Ticket Selling and Reserving System of Chinese Railway (TRS), uses the effective data mining to the passenger flow analysis, builds up the logical forecasting and analysis model. This paper firstly discusses the current situation and problems faced by forecasting of passenger flow, then applies the data warehouse technology to design the data mart of this subject. Next, samples and analyses this data which collecting in data mart adopting neural network method, builds data analysis model carrying out research and the experiment, finally puts forward a feasible forecast model for the passenger flow forecasting.
Computational Reverse Engineering Analysis for Scattering Experiments (CREASE) on Vesicles Assembled from Amphiphilic Macromolecular Solutions

In this paper we present the development and validation of the “Computational Reverse-Engineering Analysis for Scattering Experiments” (CREASE) method for analyzing scattering results from vesicle structures that are commonly found upon assembly of synthetic, biomimetic, or bioderived amphiphilic copolymers in solution. The two-step CREASE method takes the amphiphilic polymer chemistry and small-angle scattering intensity profile, Iexp(q), as input and determines the vesicles’ structural features on multiple length scales ranging from assembled vesicle wall’s individual layer thicknesses to the monomer-level packing and distribution of polymer conformations. In the first step of CREASE, a genetic algorithm (GA) is used to determine the relevant vesicle dimensions from the input macromolecular solution information and Iexp(q) by identifying the structure whose computed scattering profile best matches the input Iexp(q). Then in the second step, the GA-determined dimensions are used for molecular reconstruction of the vesicle structure. To validate CREASE for vesicles, we test CREASE on input scattering intensity profiles generated mathematically (termed as in silico Iexp(q) vs q) from a variety of vesicle sizes with known dimensions. We also test CREASE on in silico Iexp(q) vs q generated from vesicles with dispersity in all relevant dimensions, resembling real experiments. After successful validation of CREASE, we compare the CREASE-determined dimensions against those obtained from the traditional approach of fitting the scattering intensity profile to relevant analytical model in SASVIEW package. We show that CREASE performs better than or as well as the core–multishell analytical model’s fitting in SASVIEW in determining vesicle dimensions with dispersity. We also show that CREASE provides structural information beyond those possible from traditional scattering analysis using the core–multishell model, such as the distribution of solvophilic monomers between the vesicle wall’s inner and outer layers in the vesicle wall and the chain-level packing within each vesicle layer.
Analisis Kebutuhan Pengembangan E-Modul Matematika HOTS Beroerintasi Kearifan Lokal Daerah di Kelas IV Sekolah Dasar

Pandemi covid-19 berimplikasi pada pelaksanaan pembelajaran di sekolah dasar. Salah satu materi dengan ketuntasan belajar rendah yaitu pada muatan pembelajaran matematika materi bangun datar. Peserta didik memerlukan bahan ajar penunjang yang dapat memfasilitasi untuk belajar secara mandiri. Salah satu bahan ajar yang sesuai untuk permasalahan yang dialami tersebut yaitu E-modul matematika. Tujuan penelitian ini adalah melakukan analisis kebutuhan untuk pengembangan E-Modul Matematika materi bangun datar di kelas IV SD yang berorientasi HOTS dan kearifan lokal daerah Malang Raya. Metode penelitian yang digunakan adalah penelitian kualitatif dengan pendekatan deskriptif. Subjek penelitian terdiri dari 24 peserta didik dan guru kelas IV SDN Tumpang 6. Teknik pengumpulan data yang digunakan meliputi observasi, wawancara dan dokumentasi serta dilaksakan sesuai dengan prosedur penelitaian yang telah disusun peneliti. Hasil penelitian yang diawali dengan studi pendahuluan (studi pustaka dan studi lapangan), analisis kurikulum, analisis pembelajaran, analisis peserta didik, dan analisis lingkungan sekitar peserta didik menunjukkan perlu adanya pengembangan E-modul matematika yang dapat memfasilitasi peserta didik untuk belajar secara mandiri dengan didekatkan berbagai permasalahan di lingkungan sekitar
Determination of piezoelectric transducer damping by using experimental and finite element simulations

The study of piezoceramic and piezoelectric transducers behavior by finite element method (FEM) shows an important influence of viscous damping. Damping values for piezoceramic materials are not provided by manufacturers. In addition, damping values for non-piezoelectrics materials, such as, resins, steel, aluminum, etc, which are usually applied to assemble these transducers are not appropriately given for FEM simulations. Therefore, the objective of this work is to determine damping values of these materials so they can be used in a FEM software, such as, the ANSYS, which has four different ways for damping input. Damping values are determined by combining experimental and numerical techniques. For piezoceramics the damping is determined through the quality factor (Qm) by measuring the admittance curve which are influenced by damping. By using these damping values, harmonic and transient FEM simulations of piezoceramics and piezoelectric transducers are performed and the simulated admittance curve is compared with the measured one, as well as, displacement results are compared with laser interferometer measurements. Damping determination for non-piezoelectric materials are done by comparing experimental and simulated results. By using the obtained damping values, experimental measurements and simulated results for different piezoelectric transducers show a very good agreement.
Virtual Summer Undergraduate Mentorship Program for Students Underrepresented in Medicine Yields Significant Increases in Self-Efficacy Measurements During COVID-19 Pandemic: A Mixed Methods Evaluation

Purpose: The barriers that Black and Hispanic/Latinx students underrepresented in medicine (URiM) face while seeking biomedical careers have been identified, including lack of career preparation and social support. Yet it is unclear how the COVID-19 pandemic has impacted their decisions and progress toward their occupational goals. Methods: Adapting to the precautions necessitated by the COVID-19 pandemic, the authors conducted a mixed-methods evaluation of our 2020 virtual summer URiM biomedical mentoring program, using both quantitative and qualitative pre- and post-program questionnaires to measure the students' perceptions of their preparation and self-efficacy for applying to health professional schools. Results: Themes were extracted from qualitative data through thematic analysis. When students were asked how the COVID-19 pandemic affected them, two themes and subthemes emerged: (1) loss of supportive environment, (1.1) challenging learning environment, (2) derailed or uncertain future, and (2.2) COVID-19 hitting home. When students were surveyed about their online experience at the end of the program, the themes (3) supportive community and (4) inspired and reinforced goals appeared. In addition, quantitative data examined through statistical analysis revealed that the students' career self-efficacy improved significantly after program participation. Conclusion: Our results indicate that the COVID-19 pandemic has further challenged URiM students with pre-existing career obstacles. The outcomes also demonstrate that it is possible to virtually provide URiM students with socioemotional support and increase their career self-efficacy. Overall, frequent evaluations are encouraged to better understand the dynamic challenges of URiM students, improve the design of health career “pipeline” programs, and diversify the physician workforce to address racial health inequities.
Interfacial Engineering of Wide‐Bandgap Perovskites for Efficient Perovskite/CZTSSe Tandem Solar Cells

Wide‐bandgap perovskites have attracted substantial attention due to their important role in serving as a top absorber in tandem solar cells (TSCs). However, wide‐bandgap perovskite solar cells (PVSCs) typically suffer from severe non‐radiative recombination loss and therefore exhibit high open‐circuit voltage (VOC) deficits. To address these issues, a 2D octyl‐diammonium lead iodide interlayer is adopted onto the hole‐transporting layer to induce the formation of an ultrathin quasi‐2D perovskite that is close to the hole‐selective interface. This approach not only accelerates hole transfer and retards hole accumulation but also reduces the trap density in the perovskite layer on top, thereby efficiently suppresses non‐radiative recombination pathways. Consequently, the champion wide‐bandgap device (≈1.66 eV) exhibits a power conversion efficiency (PCE) of 21.05% with a VOC of 1.23 V, where the VOC deficit of 0.43 V is among the lowest values for inverted wide‐bandgap PVSCs. Moreover, by stacking a semi‐transparent perovskite top cell on a 1.1 eV Cu2ZnSn(S,Se)4 (CZTSSe) bottom cell, a 22.27% PCE was achieved on a perovskite/CZTSSe four‐terminal tandem solar cell, paving the way for all‐solution‐processed, low‐cost, and efficient TSCs with mitigated energy loss in the wide‐bandgap top cells.
Adaptive tracking of multiple sinusoids whose power levels are widely separated

The behavior of the gradient transversal filter (LMS), the gradient lattice (GL), and the least squares lattice (LSL) when used to track multiple sinusoidal (or narrow-band) components whose power levels are widely separated is investigated. These approaches to the realization of the pth-order one-step linear predictor of the time series are recursive in time. The lags of the instantaneous frequency estimates from their actual underlying values are of particular interest. The frequency tracking characteristics of the LMS, GL, and LSL algorithms are illustrated in several situations. Included are simulations of dual sinusoids undergoing a variety of frequency versus time dynamics and a formant tracking example of real speech.
High-frequency time-domain modeling of GaAs FETs using hydrodynamic model coupled with Maxwell's equations

A high frequency full wave model for microwave and millimeter wave GaAs Field Transistors (FET) is presented. The consists of two coupled models for the solid-state and electromagnetic parts of the problem. In the solid-state part, a hydrodynamic model consisting of the conservation equations for carrier density, energy, and momentum is utilized. All the conservation equations are solved with minimum simplifications. On the electromagnetic side, a 3D model consisting of Maxwell's equations is used. The time domain simulation of the device is performed using finite difference method. Numerical results of the presented model for a 0.5 /spl mu/m MESFET show that wave effect plays a crucial role in modulating fields and electron velocities inside the active device. The wave propagation is detected and found to cause considerable variations in field distribution and electron velocities. <<ETX>>
61.1: Watt Level Compact Green Laser Module for Laser Display

A watt level compact green laser based on an integrated Nd:YVO4 and MgO:PPLN module (i.e. mGreen module) is presented for the first time. A linearly polarized 532 nm laser light of 1.02 Watt is obtained, which corresponds to an optical‐to‐optical conversion efficiency of 25.5%. The mGreen module can dramatically decrease the complexity and cost of the conventional green diode pumped solid state laser.
A proficient approach for face detection and recognition using machine learning and high‐performance computing

The objective of this article is to increase the efficiency of face recognition in the aspect of a dynamic frame. Studies were carried out that focus on maintaining the high detection rate as well as increasing the accuracy. The study was conducted by considering the current recording of the dynamic frame of randomly selected people walking on a treadmill. Here, the variety of facial features was studied and extracted using different viewing angles on the subject. The existence of a huge amount of datasets and economical processing power is subject to value enhancement in the presence of a convolutional neural network (CNN) on different object identification and realization criteria. These methodologies with excellent knowledge of deep learning techniques that subjects to enhance the potential of the machine to learn the face values. CNN is capable to identify faces, positive positioning facial benchmarks, estimating postures and understanding faces in interconnected images and dynamic video frames. In this article, we present a novel phase detector technique that is rapid and has the potential of recognizing faces with huge changes. This is performed by a technique of using adopted CNN and recurrent neural network's subpart long‐short term memory technique in a particular way so that the objective of bringing improvement in the reorganization procedure can be fulfilled. And this was completed by getting 97.5%–98.1% of accuracy is sustained in this.
Sensitivity of perimeter sensor based on Sagnac interferometer

The theoretical analysis of sensitivity of the Sagnac interferometer-based sensor is presented. This setup has wide range of implementation -- one of them is a perimeter sensor for security systems. Sensor sensitivity is determined firstly by a frequency-phase sensitivity, which is connected with the interferometer principle of operation and, secondly, by electronic noise of a processing unit and attenuation of used fiber optic.
New Educational Technologies and Tools in Future Teachers’ Preparing for Professional Activities in a Multicultural Society

Ethno-cultural diversity of the population of Ukraine actualizes the problem of preparing future teachers and educators for professional activities in a multicultural society. The legislative, normative, and conceptual framework of intercultural education in Ukraine is listed. The achievements of international organizations have been taken into account and creatively developed: UN, UNESCO, UNICEF, The Council of Europe. The author’s approach to the interpretation of the essence of intercultural competence is revealed, which provides the teacher with the ability to understand and respect the cultural diversity of modern Ukrainian society, understand its value as a resource for the development of personality and society, and use in practice the educational and socializing potential of cultural diversity. The structure of the intercultural competence is outlined, which combines personal-psychological, cognitive, procedural-activity components. The model of the formation of future teachers’ intercultural competence was developed and implemented at the H. S. Skovoroda Kharkiv National Pedagogical University. The model assumes the construction of the content of the process of forming intercultural competence on the basis of a comparative acquaintance of future teachers with the traditional culture of different peoples and its implementation in the educational process, pedagogical practices, extracurricular and research activities of students; the use of innovative forms, methods and techniques of work: interactive, training, game, project; purposeful impact on the emotional sphere of the student's personality (work with moral dilemmas and multimedia resources); creation of an educational environment for intercultural communication in a pedagogical university. The media resources used in the process of forming the intercultural competence of future teachers (films of the Docudays festival, cartoons of the “Lullabies of the Worldˮ project, clips of the video project “Made in Ukraineˮ, etc.), as well as digital tools (virtual interactive whiteboards Padlet, Google Jamboard, service for creating presentations and instant polls Mentimeter, an online tool for creating interactive Wordwall games).
Combining Signal Features of Ground-Penetrating Radar to Classify Moisture Damage in Layered Building Floors

To date, the destructive extraction and analysis of drilling cores is the main possibility to obtain depth information about damaging water ingress in building floors. The time- and cost-intensive procedure constitutes an additional burden for building insurances that already list piped water damage as their largest item. With its high sensitivity for water, a ground-penetrating radar (GPR) could provide important support to approach this problem in a non-destructive way. In this research, we study the influence of moisture damage on GPR signals at different floor constructions. For this purpose, a modular specimen with interchangeable layers is developed to vary the screed and insulation material, as well as the respective layer thickness. The obtained data set is then used to investigate suitable signal features to classify three scenarios: dry, damaged insulation, and damaged screed. It was found that analyzing statistical distributions of A-scan features inside one B-scan allows for accurate classification on unknown floor constructions. Combining the features with multivariate data analysis and machine learning was the key to achieve satisfying results. The developed method provides a basis for upcoming validations on real damage cases.
Board Diversity and Financial Performance of the Nigerian Listed Firms: A Dynamic Panel Analysis

The effect of board diversity on organisational performance has continued to be given attention by policymakers, non-governmental agencies, and academic communities. It has been established that boardroom diversity enhances the corporate boards’ monitoring capacity and mitigates the agency costs, which positively influences the firms’ performance. Despite the advantages of constituting diverse boards, the corporate governance framework guiding the operations of such firms does not contain any specific requirement on board diversity. Hence, empirical studies need to stress more on the relevance of boardroom diversity to firms’ value in the Nigerian context. Therefore, this paper examines the effect of board diversity on financial performance of the Nigerian listed firms. The study utilised the balanced panel data of 70 firms for a period of 8 years (2012 to 2019) using a two-step system generalised method of moments (GMM) framework. This study indicates a positive and significant relationship of board gender diversity (BGD) and Foreign directors (FD), with financial performance. However, the effect of CEO financial expertise on the firms’ return on assets (ROA), return on equity (ROE), and return on sales (ROS) appear positive but insignificant. Consequently, the Nigerian listed firms should attach more value to constitute a smaller board size with a considerable number of female and foreign directors to maximise their performance.
Pressure-induced superconductivity in Li-Te electrides

Electrides, which accommodate excess of electrons in lattice interstitials as anions, usually exhibit interesting properties and broad applications. Until now, most electrides, especially at high pressures, show semiconducting/insulating character arising from the strong localization of interstitial and orbital electrons. However, modulating their connectivity could turn them into metals and even superconductors. In this work, with the aid of first-principles particle swarm optimization, we have identified a series of pressure-induced Li-rich electrides in the Li-Te system, in which hollow ${\mathrm{Li}}_{n}$ polyhedra accommodate the excess of electrons. With increasing Li content, these electrides undergo an interesting structural evolution. Meanwhile, the connection type of ${\mathrm{Li}}_{n}$ polyhedra experiences transitions from vertex- or edge sharing, to face sharing, leading to a diverse distribution and connectivity of interstitial electrons. All identified electrides exhibit anionic electrons-dominated metallicity. More interestingly, ${\mathrm{Li}}_{9}\mathrm{Te}$, with the highest content of ${\mathrm{Li}}_{6}$ octahedra, is superconducting with a critical temperature $({T}_{\mathrm{c}})$ of 10.2 K at 75 GPa, which is much higher than typical electrides (e.g., $12\mathrm{CaO}\ifmmode\cdot\else\textperiodcentered\fi{}7{\mathrm{Al}}_{2}{\mathrm{O}}_{3}$, ${\mathrm{Ca}}_{2}\mathrm{N}$, and ${\mathrm{Y}}_{2}\mathrm{C}$). Its superconductivity mainly originates from the coupling between hybridized electrons (anionic and atomic non-$s$-state ones) and Te-dominated phonons.
Improving wafer level CD uniformity for logic applications utilizing mask level metrology and process

Critical Dimension Uniformity (CDU) is one of the key parameters necessary to assure good performance and reliable functionality of any integrated circuit (IC). The extension of 193nm based lithography usage combined with design rule shrinkage makes process control, in particular the wafer level CDU control, an extremely important and challenging task in IC manufacturing. In this study the WLCD-CDC closed loop solution offered by Carl Zeiss SMS was examined. This solution aims to improve the wafer level intra-field CDU without the need to run wafer prints and extensive wafer CD metrology. It combines two stand-alone tools: The WLCD tool which measures CD based on aerial imaging technology while applying the exact scanner-used illumination conditions to the photomask and the CDC tool which utilizes an ultra-short femto-second laser to write intra-volume shading elements (Shade-In Elements™) inside the photomask bulk material. The CDC process changes the dose going through the photomask down to the wafer, hence the wafer level intra-field CDU improves. The objective of this study was to evaluate how CDC process is affecting the CD for different type of features and pattern density which are typical for logic and system on chip (SOC) devices. The main findings show that the linearity and proximity behavior is maintained by the CDC process and CDU and CDC Ratio (CDCR) show a linear behavior for the different feature types. Finally, it was demonstrated that the CDU errors of the targeted (critical) feature have been effectively eliminated. In addition, the CDU of all other features have been significantly improved as well.