bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lower-than-expected flare temperatures for TRAPPIST-1
Authors: Maas A. J. , Ilin E. , Oshagh M. , Pallé E. , Parviainen H. , Molaverdikhani K. , Quirrenbach A. , Esparza-Borges E. , Murgas F. , Béjar V. J. S. , Narita N. , Fukui A. , Lin C.-L. , Mori M. , Klagyivik P. 
Published: October 2022

Aims. Stellar flares emit thermal and nonthermal radiation in the X-ray and ultraviolet (UV) regime. Although high energetic radiation from flares is a potential threat to exoplanet atmospheres and may lead to surface sterilization, it might also provide the extra energy for low-mass stars needed to trigger and sustain prebiotic chemistry. Despite the UV continuum emission being constrained partly by the flare temperature, few efforts have been made to determine the flare temperature for ultra-cool M-dwarfs. We investigate two flares on TRAPPIST-1, an ultra-cool dwarf star that hosts seven exoplanets of which three lie within its habitable zone. The flares are detected in all four passbands of the MuSCAT2 instrument allowing a determination of their temperatures and bolometric energies.
Methods. We analyzed the light curves of the MuSCATl (multicolor simultaneous camera for studying atmospheres of transiting exoplanets) and MuSCAT2 instruments obtained between 2016 and 2021 in g, r, i, zs-filters. We conducted an automated flare search and visually confirmed possible flare events. The black body temperatures were inferred directly from the spectral energy distribution (SED) by extrapolating the filter-specific flux. We studied the temperature evolution, the global temperature, and the peak temperature of both flares.
Results. White-light M-dwarf flares are frequently described in the literature by a black body with a temperature of 9000–10 000 K. For the first time we infer effective black body temperatures of flares that occurred on TRAPPIST-1. The black body temperatures for the two TRAPPIST-1 flares derived from the SED are consistent with TSED = 7940−390+430 K and TSED = 6030−270+300 K. The flare black body temperatures at the peak are also calculated from the peak SED yielding TSEDp = 13 620−1220+1520 K and TSEDp = 8290−550+660 K. We update the flare frequency distribution of TRAPPIST-1 and discuss the impacts of lower black body temperatures on exoplanet habitability.
Conclusions. We show that for the ultra-cool M-dwarf TRAPPIST-1 the flare black body temperatures associated with the total continuum emission are lower and not consistent with the usually adopted assumption of 9000–10 000 K in the context of exoplanet research. For the peak emission, both flares seem to be consistent with the typical range from 9000 to 14 000 K, respectively. This could imply different and faster cooling mechanisms. Further multi-color observations are needed to investigate whether or not our observations are a general characteristic of ultra-cool M-dwarfs. This would have significant implications for the habitability of exoplanets around these stars because the UV surface flux is likely to be overestimated by the models with higher flare temperatures.
SEPIA345: A 345 GHz dual polarization heterodyne receiver channel for SEPIA at the APEX telescope
Authors: Meledin D. , Lapkin I. , Fredrixon M. , Sundin E. , Ferm S.-E. , Pavolotsky A. , Strandberg M. , Desmaris V. , López C. , Bergman P. , Olberg M. , Conway J. , Torstensson K. , Durán C. , Montenegro-Montes F. M. , De Breuck C. , Belitsky V. 
Published: October 2022

Context. We describe the new SEPIA345 heterodyne receiver channel installed at the Atacama Pathfinder EXperiment (APEX) telescope, including details of its configuration, characteristics, and test results on sky. SEPIA345 is designed and built to be a part of the Swedish ESO PI Instrument for the APEX telescope (SEPIA). This new receiver channel is suitable for very high-resolution spectroscopy and covers the frequency range 272–376 GHz. It utilizes a dual polarization sideband separating (2SB) receiver architecture, employing superconductor-isolator-superconductor mixers (SIS), and provides an intermediate frequency (IF) band of 4–12 GHz for each sideband and polarization, thus covering a total instantaneous IF bandwidth of 4 × 8 = 32 GHz.
Aims. This paper provides a description of the new receiver in terms of its hardware design, performance, and commissioning results.
Methods. The methods of design, construction, and testing of the new receiver are presented.
Results. The achieved receiver performance in terms of noise temperature, sideband rejection, stability, and other parameters are described.
Conclusions. SEPIA345 is a commissioned APEX facility instrument with state-of-the-art wideband IF performance. It has been available on the APEX telescope for science observations since July 2021.
The super-connectivity of double generalized Petersen graphs
Authors: Ekinci Gülnaz Boruzanli 
Published: October 2022

The super–connectivity of a graph G is the minimum number of vertices whose removal disconnects the graph without isolating a vertex. In this paper, we prove that the super–connectivity of double generalized Petersen graph DP(n, k) is equal to four when n ≥ 4, k ≥ 1 and n ≠ 2k.
Stellenwert der Elektrolyte und Vitamine bei
Hypertonie
Authors: Kisters Klaus , Kisters Lukas , Gröber Uwe 
Published: October 2022

ZusammenfassungHypertonie ist die häufigste internistische Erkrankung in Deutschland. In
der Behandlung haben Elektrolyte und Vitamine neben der medikamentösen
Behandlung einen hohen Stellenwert. Bedeutend ist v. a. der Einfluss von
Kochsalz (Natriumchlorid), Kalium und Magnesium, während Kalzium und
Phosphor eine untergeordnete Rolle spielen. Bei den Vitaminen sind es die
Vitamine A, C und E sowie die B-Vitamine, Vitamin D und K, die den Blutdruck
beeinflussen.
ω-3-Fettsäuren in der Kardiologie – nutzlos
oder evidenzbasiert?
Authors: Schmiedel Volker , Schmiedel Volker 
Published: October 2022

ZusammenfassungBasis der evidenzbasierten Medizin sind die kontrollierte, randomisierte,
placebo-kontrollierte Doppelblindstudie bzw. die Zusammenfassung mehrerer
solcher Studien, die Metaanalyse. In den letzten Jahren hat es – bes. in
der Sekundärprävention der KHK – eine Reihe solcher
Studien gegeben, die durchaus widersprüchliche Resultate zeigten. Neuere
Erkenntnisse belegen aber klar den Nutzen von ω-3-Fettsäuren bei
KHK.
Die Aortenklappeninsuffizienz – können wir mit interventionellen Therapieoptionen mehr Patienten helfen?
Authors: Adam Matti , Grube Eberhard 
Published: October 2022

ZusammenfassungDie hochgradige, symptomatische Aortenklappeninsuffizienz ist häufig nicht einfach zu diagnostizieren und bei einem relevanten Anteil der Patienten noch nicht ausreichend gut behandelt.
Dabei können auch Patienten mit höherem operativen Risiko von einem Aortenklappenersatz profitieren. Durch das Fortschreiten der interventionellen Therapieoptionen stellt die
Transkatheter-Aortenklappenimplantation (TAVI) mittlerweile eine ebenfalls zu berücksichtigende Therapieoption dar. Dadurch kann es möglich werden, auch ältere und kränkere Patienten einer
adäquaten und notwendigen Therapie der Aortenklappeninsuffizienz zuzuführen.
An evaluation of North Carolina science advice on COVID-19 pandemic response
Authors: Weinkle Jessica 
Published: October 2022

AbstractThis qualitative case study contributes to the international research project EScAPE (Evaluating Scientific Advice in a Pandemic Emergency) and aims to understand how state leaders mobilized science advice in pandemic response during 2020 and into the early months of 2021. North Carolina, a state in the southeastern United States, mobilized much of its pandemic science advice through the state’s Department of Health and Human Services. A fluid relationship between advisors and the governor—credited as a crucial component of a science driven, balanced pandemic response—created an opaque hub of advising and power. I analyze three advisory processes apparent during early stages of pandemic response noting strengths in mutual respect and trust between advisors and policymakers, data transparency, and commitment to equitable vaccine distribution. The interpersonal dynamics that provided these “good” science advice outcomes are a result of the individuals involved but the dynamic is not guaranteed in government over time. Also, while North Carolina provided data transparency it is unclear how data trends connected to decisions. There is a general lack of transparency around the breadth and content of advice. Transparency of advisory mechanisms is important to maintain public trust in government. Deep partisanship in the United States and distrust between leaders of opposing parties underscores the need for states to develop strong institutions for science advise to policymakers in an emergency. This article closes with several recommendations.
Emergent properties from CuPd alloy films under near-infrared excitation
Authors: Manoukian Gregory A. , Kizilkaya Orhan , Lendinez Sergi , Manuel Luis D. B. , Leite Tiago R. , Shirali Karunya S. , Shelton William A. , Sprunger Phillip T. , Baxter Jason B. , McPeak Kevin M. 
Published: October 2022

Noble-transition metal alloys offer emergent optical and electronic properties for near-infrared (NIR) optoelectronic devices. We investigate the optical and electronic properties of CuxPd1−x alloy thin films and their ultrafast electron dynamics under NIR excitation. Ultraviolet photoelectron spectroscopy measurements supported by density functional theory calculations show strong d-band hybridization between the Cu 3d and Pd 4d bands. These hybridization effects result in emergent optical properties, most apparent in the dilute Pd case. Time-resolved terahertz spectroscopy with NIR (e.g., 1550 nm) excitation displays composition-tunable electron dynamics. We posit that the negative peak in the normalized increment of transmissivity (ΔT/T) below 2 ps from dilute Pd alloys is due to non-thermalized hot-carrier generation. On the other hand, Pd-rich alloys exhibit an increase in ΔT/T due to thermalization effects upon ultrafast NIR photoexcitation. CuxPd1−x alloys in the dilute Pd regime may be a promising material for future ultrafast NIR optoelectronic devices.
A novel two-degrees of freedom (2-DOF) piezo-driven positioning platform with the working stroke being over 20 cm
Authors: Sun Qiang , Zhang Shizhong , Li Xuan , Chen Weiwei , Sun Wuxiang , Huang Hu 
Published: October 2022

Multi-degrees of freedom piezo-driven precision positioning platforms with large working strokes are demanded in many research fields. Although many multi-degrees of freedom piezo-driven positioning platforms have been proposed, few of them can achieve both large working stroke and high speed, which hinders their applications. In this study, a two-degrees of freedom piezo-driven positioning platform was proposed by stacking two identical stick–slip piezoelectric actuators. To simplify the practical implementation of a large working stroke, the actuator employed a special structure, in which the compliant mechanism and the slider were connected together as a mover and the guide rail was fixed as a stator. The working stroke of the actuator can be increased easily by increasing only the length of the guide rail without changing the output performances. By designing a lever-type compliant mechanism (LCM) on the side surface of the slider, a large loading space was obtained. Theoretical calculation and finite element analysis of the LCM were performed in detail. As the structures of these two stick–slip piezoelectric actuators are the same, only the output performances of the upper actuator (x direction) were tested as an example. Experimental results indicated that the upper actuator had a stable bi-direction motion with a working stroke being over 20 cm. The maximum speeds along the positive x and negative x directions reached 17.864 and 18.73 mm/s, and the resolutions were 100 and 230 nm, respectively. Furthermore, the vertical loading capacity was larger than 60 N.
Stunted children display ectopic small intestinal colonization by oral bacteria, which cause lipid malabsorption in experimental models
Authors: Vonaesch Pascale , Araújo João R. , Gody Jean-Chrysostome , Mbecko Jean-Robert , Sanke Hugues , Andrianonimiadana Lova , Naharimanananirina Tanteliniaina , Ningatoloum Synthia Nazita , Vondo Sonia Sandrine , Gondje Privat Bolmbaye , Rodriguez-Pozo Andre , Rakotondrainipiana Maheninasy , Kandou Kaleb Jephté Estimé , Nestoret Alison , Kapel Nathalie , Djorie Serge Ghislain , Finlay B. Brett , Wegener Parfrey Laura , Collard Jean-Marc , Randremanana Rindra Vatosoa , Sansonetti Philippe J. ,   The Afribiota Investigators, Barbot-Trystram Laurence , Barouki Robert , Bastaraud Alexandra , Collard Jean-Marc , Doria Maria , Duffy Darragh , Finlay B. Brett , Djorie Serge Ghislain , Giles-Vernick Tamara , Gondje Bolmbaye Privat , Gody Jean-Chrysostome , Hasan Milena , Hunald Francis Allen , Kapel Nathalie , Lombart Jean-Pierre , Manirakiza Alexandre , Nigatoloum Synthia Nazita , Parfrey Laura Wegener , Raharimalala Lisette , Rakotondrainipiana Maheninasy , Randremanana Rindra Vatosoa , Randriamizao Harifetra Mamy Richard , Randrianirina Frédérique , Robinson Annick , Rubbo Pierre-Alain , Sansonetti Philippe , Schaeffer Laura , Gouandjika-Vassilache Ionela , Vonaesch Pascale , Vondo Sonia Sandrine , Vigan-Womas Inès 
Published: October 2022

Environmental enteric dysfunction (EED) is an inflammatory syndrome postulated to contribute to stunted child growth and to be associated with intestinal dysbiosis and nutrient malabsorption. However, the small intestinal contributions to EED remain poorly understood. This study aimed to assess changes in the proximal and distal intestinal microbiota in the context of stunting and EED and to test for a causal role of these bacterial isolates in the underlying pathophysiology. We performed a cross-sectional study in two African countries recruiting roughly 1,000 children aged 2 to 5 years and assessed the microbiota in the stomach, duodenum, and feces. Upper gastrointestinal samples were obtained from stunted children and stratified according to stunting severity. Fecal samples were collected. We then investigated the role of clinical isolates in EED pathophysiology using tissue culture and animal models. We find that small intestinal bacterial overgrowth (SIBO) is extremely common (>80%) in stunted children. SIBO is frequently characterized by an overgrowth of oral bacteria, leading to increased permeability and inflammation and to replacement of classical small intestinal strains. These duodenal bacterial isolates decrease lipid absorption in both cultured enterocytes and mice, providing a mechanism by which they may exacerbate EED and stunting. Further, we find a specific fecal signature associated with the EED markers fecal calprotectin and alpha-antitrypsin. Our study shows a causal implication of ectopic colonization of oral bacterial isolated from the small intestine in nutrient malabsorption and gut leakiness in vitro. These findings have important therapeutic implications for modulating the microbiota through microbiota-targeted interventions.
Design of free-space couplers for suspended triangular nano-beam waveguides
Authors: Hadden J P , Maynard Cobi , Beggs Daryl M , Taylor Robert A , Bennett Anthony J 
Published: October 2022

Abstract
Photonic waveguides (WGs) with triangular cross section are being investigated for material systems such as diamond, glasses and gallium nitride, which lack easy options to create conventional rectangular nanophotonic waveguides. The design rules for optical elements in these triangular WGs, such as couplers and gratings, are not well established. Here we present simulations of elements designed to couple light into, and out of, triangular WGs from the vertical direction, which can be implemented with current angled-etch fabrication technology. The devices demonstrate coupling efficiencies approaching 50% for light focused from a high numerical aperture objective. The implementation of such couplers will enable fast and efficient testing of closely spaced integrated circuit components.
Deep multi feature dynamic adversarial diagnosis approach of rotating machinery
Authors: She Daoming , Chen Jin , Yan Xiao’an , Wang Hu , Zhang Hongfei , Pecht Michael 
Published: October 2022

Abstract
Recent works show that knowledge transfer is an effective strategy to solve cross-domain diagnosis problems. The existing domain adaptation methods considering both global and local distribution between domains do not make the most of the knowledge learned by deep neural network, resulting in low diagnosis accuracy. To solve this problem, a deep multi feature dynamic adversarial diagnosis (DMDAD) method for transfer diagnosis of rotating machinery is presented in this paper. Firstly, the one-dimensional deep convolutional neural network is utilized as the feature encoder to learn the characteristics of vibration signals in different working conditions. The class prediction vector and feature vector are fused by the multilinear mapping. The fused features are conducted for the dynamic discrimination network for adversarial training. At the same time, considering the statistical alignment and adversarial alignment, the domain adaptation is finally realized. The experimental study demonstrates the effectiveness of the DMDAD.
A novel complex network community clustering method for fault diagnosis
Authors: Chen Hongming , Lei Zihao , Tian Feiyu , Wen Guangrui , Feng Ke , Zhang Yongchao , Liu Zheng , Chen Xuefeng 
Published: October 2022

Abstract
The complex network, as a method for the analysis of nonlinear and non-stationary signals, overcomes the shortcomings of traditional time-frequency analysis methods and proves its effectiveness in mechanical fault diagnosis. Community clustering, a type of complex network, has made great progress in recent years. However, the existing community clustering algorithms have disadvantages in that they lack significant global extreme value and huge search spaces. Therefore, a Fast Newman algorithm based on reliability judgment is proposed. Starting from the community structure characteristics of the complex network, with the fault sample as a network node, the relationship between the samples as a connected edge and a complex network model of fault data is established. Clusters in troubleshooting are transformed into community structure discovery in the network. Firstly, the initial division of the community is obtained by measuring the distance between the samples. Then, the modularity index of the network is used as a standard function of the community division, and the bottom-up community merger is performed. The local edge density index is used for reliability determination before each combination to achieve global optimization, and the network block structure is the most obvious. Finally, with all the data merged into one community, the optimal division of the community structure is obtained, while accurate community clustering and fault diagnosis is realized. The benchmark graphs for testing community detection (Lancichinetti–Fortunato–Radicchi benchmark standard test network, LFR) and different fault data of rolling bearings under multiple operating conditions are applied to verify the effectiveness of this method; the results prove that the modified Fast Newman algorithm has better clustering effects and a higher accuracy rate than the original algorithm. Compared with K-means clustering and fuzzy clustering, the modified Fast Newman algorithm achieves higher performance in fault diagnosis of rolling bearings under multiple operating conditions.
Robust deep learning-based forward dose calculations for VMAT on the 1.5T MR-linac
Authors: Tsekas G , Bol G H , Raaymakers B W 
Published: October 2022

Abstract
In this work we present a framework for robust deep learning-based VMAT forward dose calculations for the 1.5T MR-linac. A convolutional neural network was trained on the dose of individual multi-leaf-collimator VMAT segments and was used to predict the dose per segment for a set of MR-linac-deliverable VMAT test plans. The training set consisted of prostate, rectal, lung and esophageal tumour data. All patients were previously treated in our clinic with VMAT on a conventional linac. The clinical data were converted to an MR-linac environment prior to training. During training time, gantry and collimator angles were randomized for each training sample, while the multi-leaf-collimator shapes were rigidly shifted to ensure robust learning. A Monte Carlo dose engine was used for the generation of the ground truth data at 1% statistical uncertainty per control point. For a set of 17 MR-linac-deliverable VMAT test plans, generated on a research treatment planning system, our method predicted highly accurate dose distributions, reporting 99.7% ± 0.5% for the full plan prediction at the 3%/3 mm gamma criterion. Additional evaluation on previously unseen IMRT patients passed all clinical requirements resulting in 99.0% ± 0.6% for the 3%/3 mm analysis. The overall performance of our method makes it a promising plan validation solution for IMRT and VMAT workflows, robust to tumour anatomies and tissue density variations.
OpenFL: the open federated learning library
Authors: Foley Patrick , Sheller Micah J , Edwards Brandon , Pati Sarthak , Riviera Walter , Sharma Mansi , Narayana Moorthy Prakash , Wang Shih-han , Martin Jason , Mirhaji Parsa , Shah Prashant , Bakas Spyridon 
Published: October 2022

AbstractObjective.Federated learning (FL) is a computational paradigm that enables organizations to collaborate on machine learning (ML) and deep learning (DL) projects without sharing sensitive data, such as patient records, financial data, or classified secrets.Approach.Open federated learning (OpenFL) framework is an open-source python-based tool for training ML/DL algorithms using the data-private collaborative learning paradigm of FL, irrespective of the use case. OpenFL works with training pipelines built with both TensorFlow and PyTorch, and can be easily extended to other ML and DL frameworks.Main results.In this manuscript, we present OpenFL and summarize its motivation and development characteristics, with the intention of facilitating its application to existing ML/DL model training in a production environment. We further provide recommendations to secure a federation using trusted execution environments to ensure explicit model security and integrity, as well as maintain data confidentiality. Finally, we describe the first real-world healthcare federations that use the OpenFL library, and highlight how it can be applied to other non-healthcare use cases.Significance.The OpenFL library is designed for real world scalability, trusted execution, and also prioritizes easy migration of centralized ML models into a federated training pipeline. Although OpenFL’s initial use case was in healthcare, it is applicable beyond this domain and is now reaching wider adoption both in research and production settings. The tool is open-sourced atgithub.com/intel/openfl.
Electron density profile reconstruction with convolutional neural networks
Authors: Lan Ting , Liu Haiqing , Ren Qilong , Zhu Xiang , Mao Wenzhe , Yuan Yi , Wang Yunfei 
Published: October 2022

Abstract
Convolutional neural networks are introduced into reconstructing electron density profiles from line-integrated density measurements of interferometers in the EAST tokamak. Diagnostic data from the polarimeter/interferometer and the hydrogen cyanide interferometer diagnostic systems are integrated to improve the reconstruction performance. By training and optimization with unreliable measurements in the data set, the robustness of this algorithm is enhanced. The established model can predict the probability distribution of density profiles accurately, fast, and robustly to noise and interference. This algorithm is not restricted to specific equilibrium configurations and can be transferred easily between different fusion devices.