Miracle-dz/UniFAR-FTUs huggingface dataset:
Solving the"many variables"problem in MICE with principal component regression

Multiple Imputation (MI) is one of the most popular approaches to addressing missing values in questionnaires and surveys. MI with multivariate imputation by chained equations (MICE) allows flexible imputation of many types of data. In MICE, for each variable under imputation, the imputer needs to specify which variables should act as predictors in the imputation model. The selection of these predictors is a difficult, but fundamental, step in the MI procedure, especially when there are many variables in a data set. In this project, we explore the use of principal component regression (PCR) as a univariate imputation method in the MICE algorithm to automatically address the"many variables"problem that arises when imputing large social science data. We compare different implementations of PCR-based MICE with a correlation-thresholding strategy by means of a Monte Carlo simulation study and a case study. We find the use of PCR on a variable-by-variable basis to perform best and that it can perform closely to expertly designed imputation procedures.
ANALYSIS AND REDUCTION OF COGGING TORQUE OF LINE-START PERMANENT MAGNET MOTORS

Compared with a standard permanent magnet synchronous motor, a line-start permanent magnet synchronous motor (LSPMSM) has additional features that include two-sided slots on its stator and rotor. Thus, due to its complex air gap form, there is no simple method to calculate the cogging torque of this kind of motor at present. This paper presents a new analytical method that models the rotor as an equivalent magnetic motive force (MMF) distribution in the air gap which avoids the influence of rotor slotting in the air gap. Based on the energy method, an analytical method is presented here to analyze the pole-slot match of stator and the influence of number of slots per pole of rotor on the cogging torque. The effect of auxiliary slots on cogging torque of LSPMSM is studied, and by changing the number of auxiliary slots to reduce the cogging torque, the correctness of the above method has been validated by the finite element method.
METODE CEPAT PEMANTAUAN HUTAN MANGROVE MENGGUNAKAN DATA PENGINDERAAN JAUH

Ekosistem mangrove merupakan ekosistem yang penting di wilayah pesisir dan bernilai baik secara ekologi maupun ekonomi. Akan tetapi ekosistem ini rentan terhadap tekanan perubahan iklim dan aktifitas manusia. Indonesia sebagai negara memiliki hutan mangrove terluas di Asia bahkan di dunia wajib mengelola kawasan mangrove dengan baik agar tetap dapat dimanfaatkan secara lestari. Salah satu informasi yang diperlukan adalah status kondisi hutan mangrove di seluruh Indonesia. Salah satu metode evaluasi yang sering digunakan adalah menggunakan informasi penurunan atau penambahan luas area kawasan mangrove. Penggunaan data penginderaan jauh menjadikan informasi akan lebih cepat disajikan untuk area yang relatif sempit, akan tetapi untuk mendapatkan informasi untuk seluruh wilayah Indonesia membutuhkan waktu, tenaga dan biaya yang cukup besar. Untuk mendapatkan informasi yang lebih cepat pada area yang sangat luas, dikembangkan metode simpel dan cepat yaitu membandingkan area kawasan mangrove dari peta yang ada sebelumnya dengan kenampakan RGB dari citra satelit terkini. Dengan metode ini bisa diperoleh informasi indikator adanya pengurangan dan penambahan kawasan mangrove dengan lebih cepat dan memungkinkan untuk dilakukan monitoring setahun sekali. Data penginderaan jauh yang digunakan dalam menggunakan metode ini adalah Landsat 8 akuisisi Tahun 2016, untuk memberikan informasi status hutan mangrove Tahun 2016. Peta yang digunakan untuk informasi eksisting hutan mangrove lama sebagai acuan adalah Peta H\hutan Mangrove keluaran Tahun 2013. Dengan menggunakan metode ini diperoleh informasi indikasi adanya pengurangan dan penambahan kawasan mangrove untuk seluruh Indonesia yang diselesaikan dalam waktu kurang dari 3 bulan dengan 5 orang pengolah data dan 1 penguji kualitas.
Control structure design with constraints for a slung load quadrotor system

We propose a control structure for a quadrotor carrying a slung load with swing-angle constraints. This quadrotor is supposed to pass through the waypoints at specified speeds. First, a cascaded PID autopilot is designed, which adaptively gives attention to position and speed requirements as a function of their errors. Its parameters are found from an optimization problem solved using the PSO algorithm. Second, this controller’s performance is improved by adding the Complementary Controller employing an ANN. 5. Training data for the ANN is created by solving optimal control problems. The ANN is activated when the swing angle constraint is about to be violated. It is trained using optimal control values corresponding to the cases where the swing angle falls in a particular band about the upper swing angle constraint. Simulations are performed in a MATLAB environment. Finally, some of the simulation results are validated on a physical system.
Identifying the 3FHL Catalog. III. Results of the CTIO-COSMOS Optical Spectroscopy Campaign

Active galactic nuclei (AGNs) with their relativistic jets pointed toward the observer form a subclass of luminous γ-ray sources commonly known as blazars. The study of blazars is essential to improve our understanding of the AGNs emission mechanisms and evolution, as well as to map the extragalactic background light. To do so, however, one needs to classify and measure a redshift for a large sample of these sources correctly. The Third Fermi-LAT Catalog of High-Energy Sources (3FHL) contains ≈1160 blazars reported at energies greater than 10 GeV. However, ∼25% of these sources are unclassified and ∼50% lack redshift information. To increase the spectral completeness of the 3FHL catalog, we are working on an optical spectroscopic follow-up campaign using 4 m and 8 m telescopes. In this paper, we present the results of the second part of this campaign, where we observed 23 blazars using the 4 m telescope at Cerro Tololo Interamerican Observatory in Chile. We report that all the 23 sources are classified as BL Lacs, a confirmed redshift measurement for three sources, a redshift lower limit for two sources, and a tentative redshift measurement for three sources.
Modélisation par champ de phases de la croissance de la ferrite allotriomorphe dans les aciers Fe-C-Mn

La ferrite allotriomorphe est une des morphologies de la ferrite dont la repartition spatiale influe fortement sur les proprietes mecaniques dans les aciers dual-phase. En fonction des traitements qu'ils subissent, la ferrite peut s'y repartir suivant les bandes de segregation en manganese, issues de l'etape de solidification. Pour etablir le role que joue le processus de croissance de la ferrite allotriomorphe sur la mise en place de la structure en bandes, nous avons developpe un modele de champ de phases possedant deux specificites originales, imposees par le probleme. D'une part, ce modele est capable de reproduire les differents regimes cinetiques observes dans les alliages ternaires Fe-C-X, pilotes par la presence concomittante du carbone diffusant rapidement,et d'un element substitutionnel X diffusant lentement. Nous avons ainsi mis en evidence la transition d'un regime initial rapide de paraequilibre vers une croissance lente en orthoequilibre, en bon accord avec des resultats experimentaux de la litterature. D'autre part, notre modele incorpore de maniere econome la presence des joints de grains austenitiques, dont le role dans l'elimination des structures en bande est souligne par nos calculs. Nous observons ainsi qu'il existe un seuil d'intensite desegregation en manganese en dessous duquel le mouillage de la ferrite le long des joints de grain de plus grande energie peut contrecarrer la croissance dans les bandes segregees negativement
Towards an all-sky radio telescope for SETI

2.22 A&G • April 2019 • Vol. 60 • aandg.org Modern SETI (the search for extra­ terrestrial intelligence) began almost six decades ago, when Drake (1961) used the 85­foot Tatel tele scope at Green Bank Observatory, West Virginia, to scan two stars over four radio chan­ nels. One interesting signal was found, but was later recognized as human­generated radio frequency interference (RFI). Almost 60 years on, our search capabilities have expanded dramatically. But so far, no unam­ biguous signs of extraterrestrial civiliza­ tions have been found. Should we give up, or must we instead cast an even wider net? Astronomers from around the world convened in Manchester, UK, from 29–31 October 2018 to explore this question. “Towards an All­Sky Radio Telescope”, supported by the University of Manchester, the Square Kilometre Array (SKA), and the Breakthrough Initiatives (sponsors of Break­ through Listen), explored the technologies and techniques that are poised to transform the search for intelligent life over the next few years. The new generation of radio telescopes coming online has an unprec­ edented combination of survey speed, sensitivity, bandwidth and resolution, and a new generation of algorithms (including machine learning approaches) is enabling new kinds of data analysis. Much of the effort in this area is focused on the SKA and its precursors, and so it was appropriate that the first day of the conference was the first meeting to take place at the new SKA Headquarters at Jodrell Bank (figure 1). It was also fitting that the meeting opened with a talk by Jocelyn Bell Burnell (University of Oxford), who described her discovery of pulsars. The dipole array telescope used by Bell Burnell has much in common, at least at first glance, with some of the new low­frequency arrays, and the survey she undertook covered the whole sky in four days. High­throughput instru­ ments are clearly important in the search for unknown types of signals. Bell Burnell described laying out charts on the floor and lining them up in right ascension to search for pulses at a given position and wondered, if the search had been computerized, whether pulsars would have been discovered. As we deal with larger and larger datasets, the importance Towards an all-sky radio telescope for SETI
Cellular Adaptation Takes Advantage of Atavistic Regression Programs during Carcinogenesis

Simple Summary Cancer can be considered the epidemic of the third millennium, and recent projections paint a worrying scenario for the coming decades. Knowledge about the causes of neoplastic transformation remains limited, and classical genetic paradigms do not provide adequate models. Likewise, current pharmacological approaches show limited efficacy and often lead to the development of drug resistance and relapse. The limited success of cancer treatments requires a revision and, possibly, a paradigm shift in how we think about the disease. In this regard, studies of tumor cell metabolism and mechanisms of tumor cell adaptation can provide important insights. Here, we review the latest knowledge on the impact of metabolic and microenvironmental conditions on determining the phenotype of tumor cells and on how increasing this understanding could improve pharmacological options. Abstract Adaptation of cancer cells to extreme microenvironmental conditions (i.e., hypoxia, high acidity, and reduced nutrient availability) contributes to cancer resilience. Furthermore, neoplastic transformation can be envisioned as an extreme adaptive response to tissue damage or chronic injury. The recent Systemic–Evolutionary Theory of the Origin of Cancer (SETOC) hypothesizes that cancer cells “revert” to “primitive” characteristics either ontogenically (embryo-like) or phylogenetically (single-celled organisms). This regression may confer robustness and maintain the disordered state of the tissue, which is a hallmark of malignancy. Changes in cancer cell metabolism during adaptation may also be the consequence of altered microenvironmental conditions, often resulting in a shift toward lactic acid fermentation. However, the mechanisms underlying the robust adaptive capacity of cancer cells remain largely unknown. In recent years, cancer cells’ metabolic flexibility has received increasing attention among researchers. Here, we focus on how changes in the microenvironment can affect cancer cell energy production and drug sensitivity. Indeed, changes in the cellular microenvironment may lead to a “shift” toward “atavistic” biologic features, such as the switch from oxidative phosphorylation (OXPHOS) to lactic acid fermentation, which can also sustain drug resistance. Finally, we point out new integrative metabolism-based pharmacological approaches and potential biomarkers for early detection.
Effects of Training Data on Prediction Model for Students' Academic Progress

—The ability to predict students’ academic performance before the start of the class with credible accuracy could significantly aid the preparation of effective teaching and learning strategies. Several studies have been conducted to enhance the performance of prediction models by emphasizing three key factors: developing effective prediction algorithms, identifying significant predictor variables, and developing preprocessing techniques. Importantly, none of these studies focused on the effect of using different types of training data on the performance of prediction models. Therefore, this study was conducted to evaluate the effects of differences in training data on the performance of a prediction model designed to monitor students’ academic progress. The findings showed that the performance of the prediction model was strongly influenced by the heterogeneity of the values of the predictor variables, which should accommodate all the existing possibilities. It was also discovered that the application of training data with different characteristics and sizes did not improve the performance of the prediction model when its heterogeneity was not representative.
On the Diversification Effect in Solvency II for Extremely Dependent Risks

In this article, we investigate the validity of diversification effect under extreme-value copulas, when the marginal risks of the portfolio are identically distributed, which can be any one having a finite endpoint or belonging to one of the three maximum domains of attraction. We show that Value-at-Risk (V@R) under extreme-value copulas is asymptotically subadditive for marginal risks with finite mean, while it is asymptotically superadditive for risks with infinite mean. Our major findings enrich and supplement the context of the second fundamental theorem of quantitative risk management in existing literature, which states that V@R of a portfolio is typically non-subadditive for non-elliptically distributed risk vectors. In particular, we now pin down when the V@R is super or subadditive depending on the heaviness of the marginal tail risk. According to our results, one can take advantages from the diversification effect for marginal risks with finite mean. This justifies the standard formula for calculating the capital requirement under Solvency II in which imperfect correlations are used for various risk exposures.
The Role of Magnetic Resonance Imaging and Computed Tomography in Spinal Cord Injury

Traumatic injuries of the spine are associated with long-term morbidity and mortality. Timely diagnosis and appropriate management of mechanical instability and spinal cord injury are important to prevent further neurologic deterioration. Spine surgeons require an understanding of the essential imaging techniques concerning the diagnosis, management, and prognosis of spinal cord injury. We present a review in the role of computed tomography (CT) including advancements in multidetector CT (MDCT), dual energy CT (DECT), and photon counting CT, and how it relates to spinal trauma. We also review magnetic resonance imaging (MRI) and some of the developed MRI based classifications for prognosticating the severity and outcome of spinal cord injury, such as diffusion weighted imaging (DWI), diffusion tractography (DTI), functional MRI (fMRI), and perfusion MRI.
Evidence and Controls of the Acceleration of the Hydrological Cycle Over Land

Investigating modifications in the hydrological cycle is essential to understand the impacts of climate change on ecosystems. This study assesses the change in the velocity of the water cycle over land at the global scale, whereas previous studies have mostly focused on changes in the atmospheric water cycle. The hydrological acceleration is quantified by a decrease in average residence time (RT) of water in the first meter of soil. The soil water RT is shown to be sensitive to the soil texture and seasonality of hydroclimatic variables. Despite substantial local variability, most of the RTs are in the range of 50–300 days. The global mean soil water RT declined at a rate of −2.30 and −0.36 days decade−1 (−1.6 to 1.0 days decade−1 the range of nine models) from 2001 to 2020 as measured by reanalysis and CMIP6 simulations for the historical scenario, respectively, which corresponds to −6.8 and −1.1 days °C−1 when expressed per degree of global warming over land. This acceleration is projected to continue at a rate of −1.35 days decade−1 (−3.4 to 0.0 days decade−1 the range of nine models) or −2.2 days °C−1 during the period 2015–2100 under the most extreme emission scenario: SSP 585. Changes in precipitation dominantly drive the acceleration of the terrestrial water cycle compared to changes in evapotranspiration. Rising temperatures and increasing carbon dioxide have opposite effects on the speed of the terrestrial water cycle with compensatory roles keeping RT relatively unchanged in the absence of PR trends.
Parameter and Topology Optimizations for Wireless Power Transfer Device Considering Magnetic and Circuit Properties

This article proposes a novel optimization method to design the transmitting and receiving coils of a wireless power transfer (WPT) device considering its magnetic and circuit properties. In the proposed optimization, the coil shapes are determined by parameter optimization (PO) for manufacturability, whereas the magnetic core shapes introduced near them are determined by topology optimization (TO). The power transfer efficiencies of the optimized WPT device are evaluated using the SPICE simulation considering the coupling with an electronic circuit. The circuit parameters of the optimized coils are computed using the homogenization-based finite element method (FEM), which can effectively evaluate the eddy current loss in the coil windings. It is shown that the optimized WPT device has a power transfer efficiency higher than 90% even when there is a misalignment.
Experimental Design of Oxidative Desulfurization of Kerosene Through Response Surface Methodology (RSM)

Sulfur compound content in fuels is one of the most undesirable pollutions regarding standard environmental regulations that demand to reduce sulfur concentration limit to 5-10% in fuels. Hence, kerosene’s oxidative desulfurization (ODS) as a model fuel (sulfur content 1158ppm) with air as an oxidant is studied. The goal of the study is to use two different synthesized nanosilica-supported catalysts, CuO/SiO2 (CAT-1) and CuO/TiO2-SiO2 (CAT-2), for the ODS of kerosene. Thirty-two experimental runs were designed via Central Composite Design (CCD) to select the experiments that will be utilized most efficiently. The analysis of variance (ANOVA) was used for statistical analysis to determine the models’ significance. The Response surface methodology (RSM) was used to determine the optimum conditions and parameters significantly affecting the response. Temperature and time are two variables studied due to their impact on oxidative desulfurization. The actual results of sulfur conversion in kerosene from lab experiments were 87% with a sulfur content of 153.3ppm and 99.22% with a sulfur content of 8.9ppm by CAT-1 and CAT-2, respectively, at conditions of 140°C and 100min. The predicted results from experimental design were 86.66% and 99.8% by CAT-1 and CAT-2 at conditions of 140°C and 100min, showing errors less than 3.1% and 1.2% for CAT-1 and CAT-2, respectively, from ANOVA. The optimal parameters of ODS were determined through the sulfur conversion maximization by numerical optimization via ANOVA. The results showed that the maximum conversion by CAT-1 was 99.5% at 140 min and 180°C, and by CAT-2 was 99.7% at 100.1 min and 140.1°C. Also, the rate data were fitted with an empirical kinetic model. The results showed that CAT-1 and CAT-2 activation energies were Ea= 28.2 kJ/mol and Ea= 38.7 kJ/mol, respectively.
Opportunities and risks of double cropping in southwestern France with a focus on soybean and sunflower crops

Growing a second food, fodder or bioenergy crop during the fallow period commonly refers to sequential double cropping or relay cropping practices, as a function of sowing date (following or within the primary crop, respectively). Such practice may generate an additional income while supplying support and regulation services. As such, it could be referred as a form of ecologically intensive agriculture but also an opportunity offered by climate change. The decision-making process in the adoption of double cropping relies on many factors related to soil and climate conditions, but also on profit expectation and risk perception. The CASDAR project “3C2A: Three crops in two years” (2019–2023) strived to create references for sequential double cropping in the South-West of France, which encompasses the regions of Nouvelle-Aquitaine and Occitanie. The project focused mainly on grain crops and raised the interest of the use of oil-protein crops such as soybean (Glycine max (L.) Merrill) and sunflower (Helianthus annuus L.) for such practice. As a preliminary contribution of 3C2A project, this paper aims at illustrating the potential interest of soybean and sunflower as double crops in the South-West of France through a qualitative analysis of farmers’ perceptions about the risks and opportunities of double-cropping completed by a 4-years on-farm evaluation of agronomic and economic performances of this practice (110 fields).