bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on microstructure, phase transformation behavior of T15 high-speed steel and the effect of adding REEs
Authors: Zhao Bo , Xia Min , Ge Chang-Chun
Published: October 2022

Rare earth elements (REEs) are a vital modifier in tool & die steel. Their effects on the phase transformation behavior, microstructure characteristics and property of as-cast T15 high-speed steel (HSS) were investigated by optical microscopy (OM), scanning electron microscopy (SEM), X-ray diffractometry (XRD), differential scanning calorimetry (DSC) and dilatometry. The experimental results show that the as-cast microstructure of samples is refined and ameliorated after adding REEs, and the total quantity of eutectic carbides with hard and brittle properties is significantly reduced, which contribute to lower Rockwell hardness levels and higher bending strength. The morphology of grain boundaries carbides turns from lamellar to blocky polygonal. During the reheating process, REEs can reduce the thermal expansion coefficient of studied steel before austenitizing and promote the dissolution of alloying elements into austenite matrix. During cooling, REEs delays the occurrence of phase transformation, but it is favorable to the increase of the expansion amount of martensite transformation. Additionally, the microhardness value also increases with the increase of cooling rate. When the cooling rate is 20 °C/s, the full martensite transformation will occur and the microhardness of HSS1 reaches the maximum value of HV738, greater than that of RE-free HSS0 (HV701).
Water modeling on slag entrainment in the slab continuous casting mold
Authors: Jiang Dongbin , Peng Xiaoxuan , Ren Ying , Yang Wen , Zhang Lifeng
Published: October 2022

A water model is built to investigate the transport phenomena in the slab continuous casting mold. The gas flow rate, casting speed, and slab width on the slag entrainment are studied. The sliver defect in the IF steel plate is analyzed by the scanning electron microscope. The slag entrainment is recorded by the high-speed camera and the velocity is measured by the PIV. The results show that sliver defects contain Al, Ca, Si, Mg, Na, and O, which are mainly derived from the mold slag entrainment. With the casting speed increase, the fluid velocity from the submerged entry nozzle rises clearly and the slag droplets detach from slag layer. As the gas flow rate increases, the liquid moves upward with bubble floating and attacks the slag-steel interface. It is suggested the gas flow rate should be less than 3.3 NL/min for the slab width of 1300 mm and the casting speed of 1.2 m/min. With the slab width increasing from 1300 mm to 1700 mm, no slag entrainment zone is reduced. The gas flow rate should be below 2.2 NL/min with the casting speed increasing to 1.4 m/min, both for the slab width of 1300 mm and 1700 mm.
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

Hypertonie 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.
Wie beeinflusst das Menschenbild unseren Umgang mit Krankheiten?
Authors: Schlenker Nila Komalasari
Published: October 2022

Unser Umgang mit Krankheiten wird beeinflusst vom Menschenbild verschiedener philosophischer Epochen. Es gibt zwei große philosophische Menschenbild-Konzepte, die sich voneinander unterscheiden. Auf der einen Seite steht das Konzept des Körper-Seele-Dualismus, das heißt die Trennung von Körper und Seele. Dieses Konzept geht auf René Descartes zurück. Das andere Konzept ist die Leib-Seele-Einheit, es wurde von Aristoteles begründet. Dieser Text will der Frage nachgehen, wie das Menschenbild unseren Umgang mit Krankheiten beeinflusst.
Einflüsse auf die Familienbildung in Bezug zu Frühgeburtlichkeit
Authors: Rohde Katrin S.
Published: October 2022

Die Familienbildungsphase ist eine prägende Zeit für alle Beteiligten – und ein Bildungsprozess im doppelten Sinn: Die Familie konstituiert sich (neu) und die Familienmitglieder erleben sich in vielfältigen Lern- und Bildungsprozessen. Besondere Herausforderungen erleben hier Familien Frühgeborener sowie schwer kranker Reifgeborener. Um sie in ihrer Situationsbewältigung zu unterstützen, braucht es fundierte und situationsorientierte Angebote der psychosozialen Begleitung, die als bedeutsam für das gesamte Familiensystem erscheint.
ω-3-Fettsäuren in der Kardiologie – nutzlos
oder evidenzbasiert?
Authors: Schmiedel Volker , Schmiedel Volker
Published: October 2022

Basis 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

Die 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

This 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.
Switchable multifunctional knob elastic metasurface for arbitrary modulation of flexural waves
Authors: Yang Zhe , Xu Weikai , Wang Wei , Yu Xiaoming
Published: October 2022

Manipulating elastic waves propagating in the desired manner has attracted substantial attention, and the metasurfaces offer the important ideas to achieve this goal. In particular, it will be more advantageous if wave function switching can be achieved without changing the microstructure of the metasurface. In the paper, a knob elastic metasurface is designed to realize the regulation of flexural wave covering the 0–2π range of phase shift by rotating the angle of the knob. When the metasurface is in the turn-on state, the angles of the knob at different positions can be adjusted reasonably though the generalized Snell's law to achieve several phenomena of anomalous refraction, beam focus, and non-paraxial self-acceleration of flexural wave in a wide frequency. And when the metasurface is placed in the turn-off state, the total reflection of the flexural wave can be realized, and then bidirectional vibration isolation can be achieved.
Distinct impacts of polar and nematic self-propulsion on active unjamming
Authors: Venkatesh Varun , Mondal Chandana , Doostmohammadi Amin
Published: October 2022

Though jamming transitions are long studied in condensed matter physics and granular systems, much less is known about active jamming (or unjamming), which commonly takes place in living materials. In this paper, we explore, by molecular dynamic simulations, the jamming–unjamming transition in a dense system of active semiflexible filaments. In particular, we characterize the distinct impact of polar vs nematic driving for different filament rigidities and at varying densities. Our results show that high densities of dynamic active filaments can be achieved by only changing the nature of the active force, nematic or polar. Interestingly, while polar driving is more effective at unjamming the system at high densities below confluency, we find that at even higher densities, nematic driving enhances unjamming compared to its polar counterpart. The effect of varying the rigidity of filaments is also significantly different in the two cases: While for nematic driving, lowering the bending rigidity unjams the system, we find an intriguing reentrant jamming–unjamming–jamming transition for polar driving as the filament rigidity is lowered. While the first transition (unjamming) is driven by softening due to reduced rigidity, the second transition (jamming) is a cooperative effect of ordering and coincides with the emergence of nematic order in the system. Together, through a generic model of self-propelled flexible filaments, our results demonstrate how tuning the nature of self-propulsion and flexibility can be employed by active materials to achieve high densities without getting jammed.
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.
Passive fluidic control on aero-optics of transonic flow over turrets with rough walls
Authors: Ren Xiang , Yu Huahua , Yao Xianghong , Su Hua , Hu Peng
Published: October 2022

In the transonic flow over a hemisphere-on-cylinder turret, strong aero-optical effects can be caused by local shock/boundary-layer interactions and separation shear layers at the turret's zenith. The effects of an annular rough wall on the passive control of fluid and aero-optics are investigated by experimental measurements and numerical simulations. The local shock/boundary-layer interaction and separated shear layer at the zenith of the turret are recorded using shadowing and Mach–Zehnder interferometer measurements. The aero-optics are measured using a Shack–Hartmann wavefront sensor. The experimental results show that the annular rough wall on the turret weakens the local shock wave, moves the flow separation point forward, and reduces the wavefront distortion at the zenith. The rough wall functions for the shear stress transport (SST) k-ω turbulence model proposed by B. Aupoix [“Roughness corrections for the k–ω shear stress transport model: Status and proposals,” J. Fluids Eng. 137, 021202 (2014)] and C.-H. Lee [“Rough boundary treatment method for the shear-stress transport k–ω model,” Eng. Appl. Comput. Fluid 12, 261–269 (2018)] are used to further study the control effect of different roughnesses. Numerical simulations based on both rough wall functions show good agreement with the experimental measurements. For various transonic flows, the steady wavefront distortions at the zenith with the rough wall at roughness ks=1 mm are 21%–50% smaller than those with smooth walls. The smaller the supersonic region, the more effective the rough wall is in reducing wavefront distortion.
Interatomic force from neural network based variational quantum Monte Carlo
Authors: Qian Yubing , Fu Weizhong , Ren Weiluo , Chen Ji
Published: October 2022

Accurate ab initio calculations are of fundamental importance in physics, chemistry, biology, and materials science, which have witnessed rapid development in the last couple of years with the help of machine learning computational techniques such as neural networks. Most of the recent efforts applying neural networks to ab initio calculation have been focusing on the energy of the system. In this study, we take a step forward and look at the interatomic force obtained with neural network wavefunction methods by implementing and testing several commonly used force estimators in variational quantum Monte Carlo (VMC). Our results show that neural network ansatz can improve the calculation of interatomic force upon traditional VMC. The relationship between the force error and the quality of the neural network, the contribution of different force terms, and the computational cost of each term is also discussed to provide guidelines for future applications. Our work demonstrates that it is promising to apply neural network wavefunction methods in simulating structures/dynamics of molecules/materials and provide training data for developing accurate force fields.
Detailed dynamics of discrete Gaussian semiflexible chains with arbitrary stiffness along the contour
Authors: Tejedor Andrés R. , Tejedor Jaime R. , Ramírez Jorge
Published: October 2022

We revisit a model of semiflexible Gaussian chains proposed by Winkler et al., solve the dynamics of the discrete description of the model, and derive exact algebraic expressions for some of the most relevant dynamical observables, such as the mean-square displacement of individual monomers, the dynamic structure factor, the end-to-end vector relaxation, and the shear stress relaxation modulus. The mathematical expressions for the dynamic structure factor are verified by comparing them with results from Brownian dynamics simulations, reporting an excellent agreement. Then, we generalize the model to linear polymer chains with arbitrary stiffness. In particular, we focus on the case of a linear polymer with stiffness that changes linearly from one end of the chain to the other, and we study the same dynamical functions previously presented. We discuss different approaches to check whether a polymer has constant or heterogeneous stiffness along its contour. Finally, we provide expressions for the Lagrangian multipliers for Gaussian chains with variable stiffness and bond length, as well as for chains with torsion-like interactions. Overall, this work presents a new insight into a well-known model for semiflexible chains and provides tools that can be exploited to explore a much broader class of polymers or compare the predictions of the model with simulations of coarse-grained semiflexible polymers.
Propagative-rhythmic membrane contraction modulated efficient micropumping of non-Newtonian fluids
Authors: Mansukhani Jaikishan , Tripathy Arijeet , Kumar Mahesh , Mondal Pranab Kumar
Published: October 2022

We here discuss a novel bioinspired pumping mechanism of non-Newtonian fluids in a microfluidic configuration, consistent with the propagative rhythmic contraction–expansion of a membrane attached to the wall of the fluidic channel. We consider the Rabinowitsch model to represent the rheology of non-Newtonian fluids. By employing lubrication theory and approximating the underlying flow to be in the creeping regime, the transport equations governing the pumping process are framed pertaining to the chosen setup. The transport equations are then evaluated by employing a well-established perturbation technique. By depicting the flow velocity components, streamline patterns, and velocity contours graphically, we aptly discuss the flow structure developed in the flow pathway and demonstrate the eventual consequence of these flow parameters to the net throughput during both compression and expansion phases of the pumping process. Finally, by demonstrating a phase-space diagram, we also discuss the impact of fluid rheology and membrane kinematics on the pumping capacity. The results obtained from the proposed model establish that the net flow owing to propagative rhythmic membrane contraction strongly relies on exponent parameter M and rheological parameter β. These consequences are expected to be of substantial practical relevance in designing micropumps intended to yield unidirectional flow of the complex fluids with improved efficiency, commonly used in biochemical/biomicrofluidic applications.
Biogenesis of telomerase RNA from a protein-coding mRNA precursor
Authors: Logeswaran Dhenugen , Li Yang , Akhter Khadiza , Podlevsky Joshua D. , Olson Tamara L. , Forsberg Katherine , Chen Julian J.-L.
Published: October 2022

Telomerase is a eukaryotic ribonucleoprotein (RNP) enzyme that adds DNA repeats onto chromosome ends to maintain genomic stability and confer cellular immortality in cancer and stem cells. The telomerase RNA (TER) component is essential for telomerase catalytic activity and provides the template for telomeric DNA synthesis. The biogenesis of TERs is extremely divergent across eukaryotic kingdoms, employing distinct types of transcription machinery and processing pathways. In ciliates and plants, TERs are transcribed by RNA polymerase III (Pol III), while animal and ascomycete fungal TERs are transcribed by RNA Pol II and share biogenesis pathways with small nucleolar RNA (snoRNA) and small nuclear RNA (snRNA), respectively. Here, we report an unprecedented messenger RNA (mRNA)-derived biogenesis pathway for the 1,291 nucleotide TER from the basidiomycete fungus
Ustilago maydis
. The
U. maydis
TER (
Um
TER) contains a 5′-monophosphate, distinct from the 5′ 2,2,7-trimethylguanosine (TMG) cap common to animal and ascomycete fungal TERs. The mature
Um
TER is processed from the 3′-untranslated region (3′-UTR) of a larger RNA precursor that possesses characteristics of mRNA including a 5′ 7-methyl-guanosine (m
7
G) cap, alternative splicing of introns, and a poly(A) tail. Moreover, this mRNA transcript encodes a protein called Early meiotic induction protein 1 (Emi1) that is conserved across dikaryotic fungi. A recombinant
Um
TER precursor expressed from an mRNA promoter is processed correctly to yield mature
Um
TER, confirming an mRNA-processing pathway for producing TER. Our findings expand the plethora of TER biogenesis mechanisms and demonstrate a pathway for producing a functional long noncoding RNA from a protein-coding mRNA precursor.
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

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

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

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

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

Objective.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

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.
Dual injection enhanced planar gate IGBT with self-adaptive hole path for better trade-off and higher SOA capability
Authors: Zhang Jinping , Huang Yunxiang , Liu Jiang , Xiao Xiang , Zhang Bo
Published: October 2022

A novel dual injection enhanced planar gate insulated gate bipolar transistor (IGBT) with self-adaptive hole path (DIE-PIGBT) is proposed. A floating-P region is applied behind the emitter-connected deep trench in z direction and contacted with the N-type carrier stored (N-CS) layer for the proposed IGBT. Compared to the conventional trench shielded planar gate IGBT (CTS-PIGBT), the proposed device further alleviates the negative impact of the N-CS layer on the breakdown voltage (BV) and reduces both the on-state voltage drop (V
ceon) and saturated collector current density (J
sat). Simulation results show that with the same device thickness of 400 μm, the BV are 4625 V and 4275 V for the proposed and conventional device, respectively. The V
ceon at 75 A cm−2 is 2.51 V for the proposed DIE-PIGBT, which is 1.13 V lower than that of the CTS-PIGBT. Furthermore, with similar BV to the conventional one, the device thickness can be reduced to 355 μm for the DIE-PIGBT. Pro. The total gate charge (Q
G) and miller plateau charge (Q
GC) for the proposed device are reduced by 61.0% and 89.9%, respectively. As a result, the proposed structure has better trade-off relationship between the V
ceon and turn-off loss (E
off). At the same V
ceon of 2.51 V, the E
off for the DIE-PIGBT and DIE-PIGBT. Pro are 45.17 mJ cm−2 and 41.01 mJ cm−2, which is reduced by 44.0% and 49.1% when compared to 80.61 mJ cm−2 of the CTS-PIGBT, respectively. Moreover, the J
sat is reduced from 619 A cm−2 for the CTS-PIGBT to 368 A cm−2 for the DIE-PIGBT under the V
ge of 15 V. The short-circuit withstand time of the DIE-PIGBT is 1.9 times larger than that of the conventional device.
Experimental observation of a dissipative phase transition in a multi-mode many-body quantum system
Authors: Benary J , Baals C , Bernhart E , Jiang J , Röhrle M , Ott H
Published: October 2022

Dissipative phase transitions are a characteristic feature of open systems. One of the paradigmatic examples for a first order dissipative phase transition is the driven nonlinear single-mode optical resonator. In this work, we study a realization with an ultracold bosonic quantum gas, which generalizes the single-mode system to many modes and stronger interactions. We measure the effective Liouvillian gap of the system and find evidence for a first order dissipative phase transition. Due to the multi-mode nature of the system, the microscopic dynamics is much richer and allows us to identify a non-equilibrium condensation process.
Microstructural characteristics of sandwiched T-shaped metamaterials for three-port splitting
Authors: Liang Guoyu , Bo Wang
Published: October 2022

This paper presents a polarization-insensitive sandwiched three-port beam splitting grating at normal incidence. The grating adopts a sandwiched structure. Based on the rigorous coupled-wave analysis (RCWA) and the simulated annealing algorithm, the grating parameters are optimized to obtain the diffraction efficiencies of 32.83% at 0th order and 32.87% at ±1st orders for transverse electric polarization, and 32.63% at 0th order and 32.39% at ±1st orders for transverse magnetic polarization. Meanwhile, the calculation results of the finite element method are in general agreement with those of RCWA. In addition, the analysis results of grating period, duty cycle, and wavelength bandwidth further demonstrate the good wavelength bandwidth of the grating and its feasibility for practical production. Therefore, the grating can be widely used in actual production.
What do artificial neural networks learn? A study for analysis of RBS spectra
Authors: Oliveira V G , Silva T F
Published: October 2022

The massive analysis of Rutherford Backscattering Spectrometry (RBS) data is complex. When the data is processed manually, it requires a long time of an experienced person. Artificial Neural Networks (ANN) can analyze, speed up, and automate data processing. In fact, after training, the ANN processes one RBS spectrum in a fraction of a second with the advantage of keeping the consistency over the whole set of spectra. Our group used ANN to process a large set of RBS spectra from the inner walls of the vacuum chamber of the W7-X fusion reactor. In this work, we used a perturbation-based method to study the local explanations of the neural network predictions. In this method, we apply small perturbations to the inputs. Then, the outputs’ variations are evaluated. Thereby activation maps were created to visualize how sensitive the ANN is to perturbations. The activation maps enable the identification of the parts of the spectrum the neural network is getting information to make predictions. Therefore, we can better understand the behavior of the machine learning model and verify if the neural network learned the features of the spectra similarly to humans.
Parton branching in the low x regime and multiplicity distributions at the LHC
Authors: Germano G. R. , Navarra F. S.
Published: October 2022

We study the multiplicity distribution measured in pp collisions at the LHC using a distribution which is derived from the Giovannini equations under the assumption that the evolution parameter is energy dependent. We obtain a negative binomial distribution with explicit energy dependence and fit it to three data sets, corresponding to different pseudorapidity and transverse momentum cuts, and also verify the applicability of the model for a fourth data set, corresponding to jets. We find a reasonable agreement with data for all sets.
A method for computing cumulants in relativistic heavy-ion collisions
Authors: Serenone Willian M , Grassi Frédérique , Hirayama Renan , Ollitrault Jean-Yves
Published: October 2022

To map QCD phase diagram is one of the greatest challenges for those who study QCD at finite temperature. A class of observables of particular interest in this study are the net-baryon cumulants. However, hydrodynamic-based hybrid models have trouble in computing higher order cumulants due to the high statistics needed. The usual oversampling procedure to increase statistics in such models does not help in this situation because it smears event-by-event fluctuations. We propose a way to compute the cumulants avoiding this issue and show its applications at LHC energies.
Monte Carlo simulations of nuclear de-excitation gamma-ray line spectra from solar flares
Authors: Szpigel Sergio , Thereza Raphael M. , Castro Carlos Guillermo Giménez de , MacKinnon Alexander L. , Simões Paulo José de Aguiar
Published: October 2022

Recently, we have demonstrated that the Monte Carlo package FLUKA can be used as an effective tool for simulating nuclear processes which occur in solar flares and that it is capable to provide a self-consistent treatment of all typical components of the γ-ray spectra observed in those events. In this work, we have employed a new simulation strategy that allows to improve statistics and resolution in energy of the generated γ-ray spectra. Using this new strategy, we have calculated spectra of γ-ray nuclear de-excitation lines produced by solar flare primary accelerated ions with typical power-law energy distributions.
Investigation of the transfer reactions induced by 16O in 27Al and 28Si at Elab = 240 MeV
Authors: Seabra C. C. , Linares R. , Zagatto V. A. B. , Cappuzzello F. , Cavallaro M. , Carbone D. , Agodi C. , Oliveira J. R. B.
Published: October 2022

In this contribution, we present first experimental results for the deuteron pickup transfer in the 16O+28Si system at E
lab. = 240 MeV. This reaction populates states in the 26Al target-like nucleus. In the same experimental campaign we have also measured the one-proton transfer 28Si(16O,17F)27Al and one-neutron transfer 27Al(16O,17O)26Al at the same beam energy. Comparison between the energy spectrum of these transfer reactions indicate that: i) the one-proton and one-neutron transfers favor the population of the low-lying states; ii) deuteron transfer to the ground state in 26Al is highly suppressed; iii) the cross-sections for deuteron transfer that populates low-lying states in 26Al are roughly 3 times less than the one-neutron transfer.
R-matrix parameters evaluation for direct and indirect kinematics data using AZURE2
Authors: Ribeiro J B , Guimaraes V , Kaur G , Zamora J C
Published: October 2022

R-matrix analyses, using the code AZURE2, were performed for the 12C+p resonant scattering data obtained in direct and inverse kinematics. Proton energy spectra in the region of the first three excited states in 13N above the 12C+p threshold were analyzed. We used two kinds of statistics data treatment to evaluate the uncertainties of the energy and widths parameter of the resonances obtained from direct and inverse kinematics spectra. Both methods indicate smaller width uncertainties from analyses of the inverse kinematics data. The correlation coefficients between resonance widths differ considerably for the direct and inverse kinematics or when analyzing direct and inverse kinematics data simultaneously.
Damping of Mott oscillations as a guide for planning a 6Li +6 Li scattering experiment
Authors: Angelo M B , Guimarães V , Assunção M , Canto L F , Lubian J
Published: October 2022

Mott oscillations are a quantum oscillation pattern observed in angular distributions of identical particle scatterings. When both incident and target particles are bosons (integer spin), there are energies at which Mott oscillations are damped around 90° in the center-of-mass frame, a phenomenon called Transverse Isotropy (TI). Different optical potentials predict different TI energies, so TI energy measurements can provide insight into nucleus-nucleus interaction. Data on angular distributions for identical scattering of 6Li nuclei (s = 1) is available in the literature but at very limited values of energies and angular range. We have analyzed some of these angular distributions with the Fresco code, considering Woods-Saxon potentials in the calculations, and have emphasized the importance of conducting an experiment of our own.
TCAD Simulation of Single Event Effects on Electronic Devices
Authors: Buhler R. T. , Novo C. , Perin A. L. , Galeti M. , Pereira C. F. , Guazzelli M. A. , Giacomini R. C.
Published: October 2022

In this paper, lateral bulk PIN photodiodes designed at FEI University and SOI (Silicon-on-Insulator) PIN photodiodes from UCL are analyzed as photodetectors and SEE (Single Event Effects) sensors. Numerical simulations are used for radiation analysis of heavy ion striking the PIN photodiode using the parameters extracted by real measurements in a non-radiation condition. The occurrence of SEE near-Earth natural environment is unpredictable and is a serious threat that can lead to malfunctions of microprocessors, memory banks and devices that are vital to the correct behavior of a low-orbit or avionic mission. Detecting their occurrence and monitoring the energetic particles in radiation environments is vital and this paper investigates the consequence of SEE on lateral PIN photodiodes through experimentally calibrated TCAD numerical simulations.
Modelling on the synergy of mechanical and electrical wear in a current line/catenary-pantograph system
Authors: Lee C Y , Huang C H , Lin H E , Lin J Y , Yu S P , Yang Y L , Huang H H
Published: October 2022

The metro system of electrified rolling stock is an important vehicle for partly solving the metropolitan transportation and carbon emission problems. This study aims to analyse the wear of current collector/catenary-pantograph system in the rolling stock. A theoretical wear rate model between the conductor wire and the current collector of the pantograph system was adopted from the literature and further decomposed into mechanical load, electrical current, current arc erosion, and the synergy components. Based on the decomposed model, an experimental protocol for finding the curve-fitted parameters for the theoretical model was proposed. The numerical data adopted from a previous literature was employed in the decomposed model to discuss the effects of mechanical loading, electrical current, and vehicle speed on the wear rate components. From the decomposed wear rate model, the so-called electrical current lubrication on the total wear rate due to the applied electrical current could be observed directly. Moreover, the nonlinear couplings among the control factors in the operation of the system manifested significantly. Thus, in the design phase the optimization analysis should be performed on the control parameters using the theoretical wear rate model to extend the life and reliability of this catenary-pantograph system.
Multiple-object segmentation by using a destructive 3D digitizer
Authors: Lee W C , Jiang C S
Published: October 2022

A destructive 3D digitizer is a practical tool in reverse engineering. It acquires images of the cross-sections of an object layer by layer. Then the desired portions of the images will be segmented to reconstruct a CAD model. While the threshold method was helpful to segment images containing a single object, it led to a substantial error for images containing multiple objects due to the reflection between objects. This study incorporated the least square method into image processing to correct reflection error for multiple-object reconstruction. As illustrated in the case study, we successfully removed the material reflection errors, which ranged from 4.5% to 19% of the total thickness of the reconstructed CAD model.