bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adverse Outcomes during Postpartum Readmissions after Deliveries Complicated by Hypertensive Disorders of Pregnancy
Authors: Emeruwa Ukachi N. , Gyamfi-Bannerman Cynthia , Wen Timothy , Booker Whitney , Wright Jason D. , Huang Yongmei , D'Alton Mary E. , Friedman Alexander M. 
Published: November 2021

Objective This study aimed to characterize risk for postpartum complications based on specific hypertensive diagnosis at delivery.
Study Design This retrospective cohort study used the 2010 to 2014 Nationwide Readmissions Database to identify 60-day postpartum readmissions. Delivery hospitalizations were categorized based on hypertensive diagnoses as follows: (1) preeclampsia with severe features, (2) superimposed preeclampsia, (3) chronic hypertension, (4) preeclampsia without severe features, (5) gestational hypertension, or (6) no hypertensive diagnosis. Risks for 60-day readmission was determined based on hypertensive diagnosis at delivery. The following adverse outcomes during readmissions were analyzed: (1) stroke, (2) pulmonary edema and heart failure, (3) eclampsia, and (4) severe maternal morbidity (SMM). We fit multivariable log-linear regression models to assess the magnitude of association between hypertensive diagnoses at delivery and risks for readmission and associated complications with adjusted risk ratios (aRR) as measures of effect.
Results From 2010 to 2014, 15.7 million estimated delivery hospitalizations were included in the analysis. Overall risk for 60-day postpartum readmission was the highest among women with superimposed preeclampsia (6.6%), followed by preeclampsia with severe features (5.2%), chronic hypertension (4.0%), preeclampsia without severe features (3.9%), gestational hypertension (2.9%), and women without a hypertensive diagnosis (1.5%). In adjusted analyses for pulmonary edema and heart failure as the outcome, risks were the highest for preeclampsia with severe features (aRR = 7.82, 95% confidence interval [CI]: 6.03, 10.14), superimposed preeclampsia (aRR = 8.21, 95% CI: 5.79, 11.63), and preeclampsia without severe features (aRR = 8.87, 95% CI: 7.06, 11.15). In the adjusted model for stroke, risks were similarly highest for these three hypertensive diagnoses. Evaluating risks for SMM during postpartum readmission, chronic hypertension and superimposed preeclampsia were associated with the highest risks.
Conclusion Chronic hypertension was associated with increased risk for a broad range of adverse postpartum outcomes. Risk estimates associated with chronic hypertension with and without superimposed preeclampsia were similar to preeclampsia with severe features for several outcomes.
Key Points
Empirical asset pricing via machine learning: evidence from the European stock market
Authors: Drobetz Wolfgang , Otto Tizian 
Published: November 2021

AbstractThis paper evaluates the predictive performance of machine learning methods in forecasting European stock returns. Compared to a linear benchmark model, interactions and nonlinear effects help improve the predictive performance. But machine learning models must be adequately trained and tuned to overcome the high dimensionality problem and to avoid overfitting. Across all machine learning methods, the most important predictors are based on price trends and fundamental signals from valuation ratios. However, the models exhibit substantial variation in statistical predictive performance that translate into pronounced differences in economic profitability. The return and risk measures of long-only trading strategies indicate that machine learning models produce sizeable gains relative to our benchmark. Neural networks perform best, also after accounting for transaction costs. A classification-based portfolio formation, utilizing a support vector machine that avoids estimating stock-level expected returns, performs even better than the neural network architecture.
Physics on a Playground
Authors: Mårtensson-Pendrill Ann-Marie 
Published: November 2021

A playground visit can be used to support the teaching about force and motion at different levels, from preschool to university. It can also be used as a preparation for amusement park physics days. A playground visit gives easier access and more freedom to experiment with the motion and with different objects than amusement park rides.
The chapter starts with a presentation of investigations on a small playground with climbing racks, slides, and swings. This introduction is followed by brief discussions of possibilities on large playgrounds, including parabolic whispering dishes, see-saws, carousels, spinning bowls, and trampolines. Thematic investigations to integrate playground experiences into the curriculum are suggested for several concepts: equivalence between gravitational and inertial mass (the equivalence principle); torque and angular momentum; work and energy as well as friction and rolling on inclined planes. Finally, the organization of playground teacher days is discussed to support sharing the joy of physics with teachers for younger students.
Introns encode dsRNAs undetected by RIG-I/MDA5/interferons and sensed via RNase L
Authors: Chitrakar Alisha , Solorio-Kirpichyan Kristina , Prangley Eliza , Rath Sneha , Du Jin , Korennykh Alexei 
Published: November 2021

Significance
Double-stranded RNA (dsRNA) is the strongest-known “molecular signature” of viral infections that activates antiviral interferon responses and inflammation in human cells. Due to this activity, dsRNA-sensing pathways belong to the core interests of academic laboratories and pharma working on antiviral defenses and inflammatory diseases. dsRNAs do not always arise from viral infections. Mammalian cells can also produce their own dsRNAs. Precisely what are the endogenous dsRNAs that activate innate immune responses in human cells, and which receptors of the innate immune system sense endo-dsRNAs? Here, we find that human endo-dsRNAs can arise from jammed decay of intronic and intergenic transcripts folded as RNA duplexes. We show that the receptors OAS3/RNase L and PKR are important sensors of these dsRNAs.
What do (some of) our association measures measure (most)? Association?
Authors: Gries Stefan Th. 
Published: November 2021

AbstractThis paper discusses the degree to which some of the most widely-used measures of association in corpus linguistics are not particularly valid in the sense of actually measuring association rather than some amalgam of a lot of frequency and a little association. The paper demonstrates these issues on the basis of hypothetical and actual corpus data and outlines implications of the findings. I then outline how to design an association measure that only measures association and show that its behavior supports the use of the log odds ratio as a true association-only measure but separately from frequency; in addition, this paper sets the stage for an analogous review of dispersion measures in corpus linguistics.
Generative adversarial network and transfer-learning-based fault detection for rotating machinery with imbalanced data condition
Authors: Li Jun , Liu Yongbao , Li Qijie 
Published: November 2021

Abstract
Intelligent fault diagnosis achieves tremendous success in machine fault diagnosis because of its outstanding data-driven capability. However, the severely imbalanced dataset in practical scenarios of industrial rotating machinery is still a big challenge for the development of intelligent fault diagnosis methods. In this paper, we solve this issue by constructing a novel deep learning model incorporated with a transfer learning (TL) method based on the time-generative adversarial network (Time-GAN) and efficient-net models. Firstly, the proposed model, called Time-GAN-TL, extends the imbalanced fault diagnosis of rolling bearings using time-series GAN. Secondly, balanced vibration signals are converted into two-dimensional images for training and classification by implementing the efficient-net into the transfer learning method. Finally, the proposed method is validated using two types of rolling bearing experimental data. The high-precision diagnosis results of the transfer learning experiments and the comparison with other representative fault diagnosis classification methods reveal the efficiency, reliability, and generalization performance of the presented model.
Enhanced terahertz emission from mushroom-shaped InAs nanowire network induced by linear and nonlinear optical effects
Authors: Xi Fugang , Yang He , Khayrudinov Vladislav , He Yuhang , Haggren Tuomas , Zhou Yixuan , Lipsanen Harri , Sun Zhipei , Xu Xinlong 
Published: November 2021

Abstract
The development of powerful terahertz (THz) emitters is the cornerstone for future THz applications, such as communication, medical biology, non-destructive inspection, and scientific research. Here, we report the THz emission properties and mechanisms of mushroom-shaped InAs nanowire (NW) network using linearly polarized laser excitation. By investigating the dependence of THz signal to the incidence pump light properties (e.g. incident angle, direction, fluence, and polarization angle), we conclude that the THz wave emission from the InAs NW network is induced by the combination of linear and nonlinear optical effects. The former is a transient photocurrent accelerated by the photo-Dember field, while the latter is related to the resonant optical rectification effect. Moreover, the p-polarized THz wave emission component is governed by the linear optical effect with a proportion of ∼85% and the nonlinear optical effect of ∼15%. In comparison, the s-polarized THz wave emission component is mainly decided by the nonlinear optical effect. The THz emission is speculated to be enhanced by the localized surface plasmon resonance absorption of the In droplets on top of the NWs. This work verifies the nonlinear optical mechanism in the THz generation of semiconductor NWs and provides an enlightening reference for the structural design of powerful and flexible THz surface and interface emitters in transmission geometry.
Exploring electron beam induced atomic assembly via reinforcement learning in a molecular dynamics environment
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Authors: Vasudevan Rama K , Ghosh Ayana , Ziatdinov Maxim , Kalinin Sergei V 
Published: November 2021

Abstract
Atom-by-atom assembly of functional materials and devices is perceived as one of the ultimate targets of nanotechnology. Recently it has been shown that the beam of a scanning transmission electron microscope can be used for targeted manipulation of individual atoms. However, the process is highly dynamic in nature rendering control difficult. One possible solution is to instead train artificial agents to perform the atomic manipulation in an automated manner without need for human intervention. As a first step to realizing this goal, we explore how artificial agents can be trained for atomic manipulation in a simplified molecular dynamics environment of graphene with Si dopants, using reinforcement learning. We find that it is possible to engineer the reward function of the agent in such a way as to encourage formation of local clusters of dopants under different constraints. This study shows the potential for reinforcement learning in nanoscale fabrication, and crucially, that the dynamics learned by agents encode specific elements of important physics that can be learned.
Effects of secondary γ-electrons from accelerator grid under ion impingement in gridded ion sources
Authors: Fu S H , Tian L C , Ding Z F 
Published: November 2021

Abstract
Thus far, effects of secondary γ-electrons emitted from accelerator grids (AGs) of gridded ion sources on ionization in discharge chambers have not been studied. The presence and induced processes of such secondary electrons in a microwave electron cyclotron resonance gridded ion source are confirmed by the consistent explanations of: (1) the observed jump of ion beam current (I
b) in case of a low-density plasma appearing at the chamber’s radial center due to the microwave skin effect; (2) the evolution of glow images recorded from the end-view of the ion source during the jump of I
b; (3) the over-large jump step of I
b with increasing microwave power; (4) the pattern appearing on the temperature sticker exposed to the discharge operated in the regime where the arrayed energetic-electron beamlets are injected into the discharge chamber; (5) the measured step-increment in the voltage drop across the screen grid (SG) sheath. A positive feedback loop composed of involved processes is established to elucidate the underlying mechanism. Energetic γ-electrons from the AG and warm δ-electrons from the opposite antenna do not produce direct excitation and ionization, but they enhance the electrical confinement of cold electrons by elevating the voltage drop across the sheaths at the antenna and SG, thus leading to the jump of I
b. The energetic γ-electrons-based model can be also modified to explain abnormal results observed in the other gridded ion sources. Energetic γ-electrons from AGs should be taken into account in understanding gridded ion sources.
Manipulation of wave motion in smart nonlinear phononic crystals made of shape memory alloys
Authors: Sepehri Soroush , Mosavi Mashhadi Mahmoud , Seyyed Fakhrabadi Mir Masoud 
Published: November 2021

Abstract
Thanks to the functional role of shape memory alloys (SMAs) in controlling the mechanical behavior of structures, researchers have started investigating the possibility of manipulating wave motion in phononic crystals using SMAs. While SMAs were used before to tune the wave propagation in linear phononic crystals, in this work, we aim to extend their utilization to nonlinear lattices. For this purpose, SMA helical springs are used to manipulate the dispersion curves and the location of stop-bands in weakly nonlinear monoatomic and diatomic lattice chains. Using Brinson’s formulation to describe the thermo-mechanical behavior of SMA wires and Lindstedt-Poincaré method to solve the derived governing equations, closed-form nonlinear dispersion relations in monoatomic and diatomic lattice chains are obtained and the effects of temperature-induced phase transformation and stiffness nonlinearity on the wave propagation are investigated. The results reveal that the dispersion curves of a weakly nonlinear monoatomic chain are formed at lower frequencies through the austenite-to-martensite phase transformation. Similarly, both the acoustic and optical branches of a diatomic lattice are moved to lower frequencies during the phase transformation in the cooling process. Therefore, the generated stop-bands in nonlinear diatomic lattices are also moved to lower frequencies. In addition, using auxiliary SMA ground springs, new classes of nonlinear monoatomic and diatomic chains exhibiting additional low-frequency attenuation zones are introduced. These low-frequency stop-bands are tunable and their frequency range can be modulated by exploiting the temperature-induced phase transformation in the SMA springs. The results obtained from analytic formulations are verified by numerical calculations and an excellent agreement is observed. Such tunability and the potential for adding stop-bands in low frequencies reveal that SMAs can be very helpful in designing nonlinear phononic and acoustic devices, such as vibration mitigators and wave filters with pre-defined attenuation zones.
Unified galaxy power spectrum measurements from 6dFGS, BOSS, and eBOSS
Authors: Beutler Florian , McDonald Patrick 
Published: November 2021

Abstract
We make use of recent developments in the analysis of galaxy
redshift surveys to present an easy to use matrix-based analysis
framework for the galaxy power spectrum multipoles, including
wide-angle effects and the survey window function. We employ this
framework to derive the deconvolved power spectrum multipoles of
6dFGS DR3, BOSS DR12 and the eBOSS DR16 quasar sample. As an
alternative to the standard analysis, the deconvolved power spectrum
multipoles can be used to perform a data analysis agnostic of survey
specific aspects, like the window function. We show that in the
case of the BOSS dataset, the Baryon Acoustic Oscillation (BAO)
analysis using the deconvolved power spectra results in the same
likelihood as the standard analysis. To facilitate the analysis
based on both the convolved and deconvolved power spectrum
measurements, we provide the window function matrices, wide-angle
matrices, covariance matrices and the power spectrum multipole
measurements for the datasets mentioned above. Together with this
paper we publish a Python-based toolbox to calculate the
different analysis components. The appendix contains a detailed
user guide with examples for how a cosmological analysis of these
datasets could be implemented. We hope that our work makes the
analysis of galaxy survey datasets more accessible to the wider
cosmology community.
Proximate Analysis and Antioxidant Activity of Red Rice (Oryza sativa L.) Milk
Authors: Wijaya Cokro , Romulo Andreas 
Published: November 2021

Abstract
Plant-based milk has become a consumer interest in recent years due to the health-beneficial effect of the product. Red rice milk is one of the cereal-based milk that uses red rice (Oryza sativa L.) as the main ingredient that contains antioxidant activity. The utilization of red rice in Indonesia is very limited, only for replacing white rice. The potency of red rice to be developed as rice milk has been poorly studied about the antioxidant activity and proximate content in the red rice milk. In this research, red rice was used as the main ingredient. Proximate analysis and antioxidant analysis (DPPH and total phenolic content) were conducted on the red rice milk. This research aims to analyze the nutrients content in red rice milk and its antioxidant activity. Red rice milk contained 98.01% of water, 0.07% of ash, 0.13% of protein, 0.71% of fat, and 1.07% of carbohydrate. Red rice milk inhibited 53.37% of DPPH radical and contained total phenolic about 274.5 ppm. The result revealed the potential of red rice milk as a functional drink with antioxidants.
Simple Amperometric Biosensor for Sucrose Concentration Measurement Based on Principal Component Analysis
Authors: Rosandi Vira Annisa , Linda Tetty Marta , Agustirandi Beny , Umar Lazuardi 
Published: November 2021

Abstract
Sucrose is a type of sugar that is widely used in various types of foods and beverages. In Indonesia, sucrose consumption reaches 2.8 million tons on average per year. Effects of consuming too much sucrose can increase the risk of various diseases such as diabetes, dental caries and obesity. The level of maximum amount of sucrose that is safe for the body equal to 10% of the total energy or the equivalent of 50 g/person/day, so that the required detection system and the identification of the sucrose concentration. In this work, the identification process was carried out using an amperometric biosensor based on the yeast Saccharomyces cerevisiae as a bioreceptor. Measurements were made by immobilizing yeast cells and analyte samples into the biosensor electrodes and observed based on cellular respiration activity which was expressed as a parameter of dissolved oxygen (DO). The biosensor response is generated in the form of an output potential value, then processed using principal component analysis (PCA) to produce a sucrose concentration classification point with a percentage of variance of the two main components of 98.77% which states that the sensor is able to identify sucrose concentrations.
High Potential of Averrhoa bilimbi Leaf Waste as Porous Activated Carbon Source for Sustainable Electrode Material Supercapacitor
Authors: Taer E , Nursyafni  , Apriwandi  , Taslim R 
Published: November 2021

Abstract
The energy cost-effective/free-environmental pollution concerns have an interest in bio-waste materials for the production of porous activated carbon, especially as electrode material for electrochemical energy storage devices such as li-ion batteries and supercapacitors. In this study, Averrhoa bilimbi leaf wastes were selected as a porous activated carbon source for sustainable electrode material supercapacitor. Porous activated carbons were prepared by chemical activation of 0.5 ml−1 sodium hydroxide solution at an optimum temperature of 800 °C pyrolyze in an environment of N2 and CO2 gases. The monolith coin shape of activated carbon is maintained by optimizing the self-adhesive properties of the precursor without the addition of adhesive materials. All coin monoliths feature a turbostratic to highly amorphous carbon structure. Furthermore, the relatively high monolith dimensional shrinkage of 42.00% initiated the development of a better pore framework carbon. In symmetric supercapacitors, electrochemical behavior confirmed a high specific capacitance of 149.04 F/g at a constant density of 1.0 A/g. Moreover, the maximum energy density was found of 10.50 Whkg−1 at an optimum power density of 116.35 W/kg in an aqueous electrolyte of 1 ml−1 Na2SO4. With bio-recycled waste, relatively easy preparation, and high electrochemical properties, porous activated carbon based on Averrhoa bilimbi leaf has great potential as a sustainable electrode material for supercapacitor energy storage applications.
Etlingera elatior leaf agricultural waste as activated carbon monolith for supercapacitor electrodes
Authors: Taer E , Padang E , Yanti N , Apriwandi  , Taslim R 
Published: November 2021

Abstract
Recently, biomass waste has become the focus of several researchers because it has promising potential when processed into porous activated carbon. Abundant availability, uncomplicated processing, and more economical are the reasons for choosing biomass as the basic material for making carbon electrodes for electric energy storage supercapacitors. In this study, Etlingera elatior waste biomass is processed into activated carbon by heating at high temperature and impregnation of 0.5 M ZnCl2. The monolith sample was optimized through a single-stage integrated high-temperature pyrolysis process. Where the process of carbonization of N2 gas from a temperature of 30 °C to 600 °C followed by a physical activation process of CO2 gas to a temperature of 800 °C. Determination of the physical properties of the electrodes through density characterization, while the electrochemical properties were analyzed by cyclic voltammetry and galvanostatic charge discharge methods. Cyclic voltammetry and galvanostatic charge discharge analysis were performed with 1 M Na2SO4 aqueous electrolyte at a voltage of 0–1 V and a scan rate of 1 mV/s. Furthermore, the high electrochemical behavior of the CV method was found to be 108 F/g, while for the gcd method, the specific capacitance was much higher at 148 F/g at a constant current density of 1.0 A/g. Further calculations found an energy density of 8.23 Wh/kg and a power density of 161 W/kg. These results support the optimization of 0.5 M ZnCl2 impregnated Etlingera elatior leaves as the base material for activated carbon electrodes to increase the supercapacitor capacitance.