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Violent collisions can reveal hexadecapole deformation of nuclei

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Nuclear Science and Techniques 2024年第7期35卷 1-3页

作者： Björn Schenke Physics Department Brookhaven National LaboratoryUptonNY 11973USA

A new observable in heavy ion collision experiments was identified to be sensitive to the hexadecapole deformation of the colliding *** deformation is difficult to measure in traditional nuclear electric transition measurements,as it is often overwhelmed by the nuclear quadrupole *** opens the door to gain new insight into nuclear structure with experiments that were designed to study hot and dense nuclear matter.

关键词： deformation collision insight

Violent collisions can reveal hexadecapole deformation of nuclei

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Nuclear Science and Techniques 2024年第7期 70-72页

作者： Bj?rn Schenke Physics Department Brookhaven National Laboratory

A new observable in heavy ion collision experiments was identified to be sensitive to the hexadecapole deformation of the colliding nuclei. Such deformation is difficult to measure in traditional nuclear electric transition measurements, as it is often overwhelmed by the nuclear quadrupole deformation. This opens the door to gain new insight into nuclear structure with experiments that were designed to study hot and dense nuclear *** structures are determined by the nuclear force, providing fundamental insight into the laws of nature. Deformations,quantifiedbydeviationsfromasphericalshape,area consequence of the interaction between the nuclear shell structure and the residual valence nucleons, whose detailed knowledge is crucial for understanding for example nucleosynthesis,nuclearfission,andneutrinolessdouble-beta decay.

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Accelerated design of high-performance Mg-Mn-based magnesium alloys based on novel bayesian optimization

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Journal of Magnesium and Alloys 2024年第2期12卷 750-766页

作者： Xiaoxi Mi Lili Dai Xuerui Jing Jia She Bjørn Holmedal Aitao Tang Fusheng Pan College of Materials Science and Engineering Chongqing UniversityChongqing 400044China Southwest Technology and Engineering Research Institute Chongqing 400039China National Engineering Research Center for Magnesium Alloys Chongqing UniversityChongqing 400044China Department of Materials Science and Engineering Norwegian University of Science and Technology(NTNU)Trondheim 7051Norway

Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various *** development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial *** the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg *** paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought *** employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy *** model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design *** RBOALM,several new high-performance alloys have been successfully designed and ***,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture ***,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.

关键词： Mg-Mn-based alloys High-performance Alloy design Machine learning Bayesian optimization

Development of bismuth-based solutions for well plugging and abandonment:A review

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Petroleum Research 2024年第2期9卷 250-264页

作者： Lewaa Hmadeh Marcelo Anunciação Jaculli Behzad Elahifar Sigbjørn Sangesland Norwegian University of Science and Technology PTSValgrindaS.P.Andersens veg 15 ANorway

Plugging and abandonment(P&A)is a crucial step of the well life *** of how long one stretches the productive life of a well,P&A operations will have to be carried out *** current panorama of our industry includes many wells to be plugged and abandoned,with steep requirements to abide by both regulations and societal *** this context,we must guarantee that no leakage occurs with an eternal perspective in *** has been the prime material for this task,but recent studies have indicated the potential of degradation over time-especially in corrosive environments-and the creation of leaking paths due to its *** has opened up a path toward the usage of alternative *** of the emerging candidates is bismuth,a metal with the unique characteristic of expanding when *** a trait could improve the overall sealability of wellbores and especially during P&*** article discusses the current status of bismuth sealing technologies,introducing the basics of bismuth,the ongoing efforts to qualify it as a barrier material,its potential applications,and the challenges that still need to be *** latest research indicates promising results in terms of its usage as a barrier element.

关键词： Bismuth plugs Bismuth-tin alloys Well plugging and abandonment Well integrity

Flood Velocity Prediction Using Deep Learning Approach

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Journal of Geodesy and Geoinformation Science 2024年第1期7卷 59-73页

作者： LUO Shaohua DING Linfang TEKLE Gebretsadik Mulubirhan BRULAND Oddbjørn FAN Hongchao Department of Civil and Environmental Engineering Norwegian University of Science and TechnologyTrondheim 7034Norway

Floods are one of the most serious natural disasters that can cause huge societal and economic *** research has been conducted on topics like flood monitoring,prediction,and loss *** these research fields,flood velocity plays a crucial role and is an important factor that influences the reliability of the *** methods rely on physical models for flood simulation and prediction and could generate accurate results but often take a long *** learning technology has recently shown significant potential in the same field,especially in terms of efficiency,helping to overcome the time-consuming associated with traditional *** study explores the potential of deep learning models in predicting flood *** specifically,we use a Multi-Layer Perceptron(MLP)model,a specific type of Artificial Neural Networks(ANNs),to predict the velocity in the test area of the Lundesokna River in Norway with diverse terrain *** data and flood velocity simulated based on the physical hydraulic model are used in the study for the pre-training,optimization,and testing of the MLP *** experiment indicates that the MLP model has the potential to predict flood velocity in diverse terrain conditions of the river with acceptable accuracy against simulated velocity results but with a significant decrease in training time and testing ***,we discuss the limitations for the improvement in future work.

关键词： flood velocity prediction geographic data MLP deep learning

Detecting somatisation disorder via speech:introducing the Shenzhen Somatisation Speech Corpus

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Intelligent Medicine 2024年第2期4卷 96-103页

作者： Kun Qian Ruolan Huang Zhihao Bao Yang Tan Zhonghao Zhao Mengkai Sun Bin Hu Björn W.Schuller Yoshiharu Yamamoto Key Laboratory of Brain Health Intelligent Evaluation and Intervention Ministry of EducationBeijing Institute of TechnologyBeijing 100081China School of Medical Technology Beijing Institute of TechnologyBeijing 100081China The First School of Clinical Medicine Southern Medical UniversityGuangzhouGuangdong 510515China Department of Neurology Shenzhen University General HospitalShenzhenGuangdong 518055China Group on Language Audio&MusicImperial College LondonLondon SW72AZUK Embedded Intelligence for Health Care and Wellbeing University of AugsburgAugsburg 86159Germany Educational Physiology Laboratory Graduate School of EducationThe University of TokyoTokyo 113-0033Japan

Objective Speech recognition technology is widely used as a mature technical approach in many *** the study of depression recognition,speech signals are commonly used due to their convenience and ease of *** speech recognition is popular in the research field of depression recognition,it has been little studied in somatisation disorder *** reason for this is the lack of a publicly accessible database of relevant speech and benchmark *** this end,we introduced our somatisation disorder speech database and gave benchmark *** By collecting speech samples of somatisation disorder patients,in cooperation with the Shenzhen University General Hospital,we introduced our somatisation disorder speech database,the Shenzhen Somatisation Speech Corpus(SSSC).Moreover,a benchmark for SSSC using classic acoustic features and a machine learning model was proposed in our *** To obtain a more scientific benchmark,we compared and analysed the performance of different acoustic features,i.e.,the full ComPare feature set,or only Mel frequency cepstral coefficients(MFCCs),fundamental frequency(F0),and frequency and bandwidth of the formants(F1-F3).By comparison,the best result of our benchmark was the 76.0%unweighted average recall achieved by a support vector machine with formants F1–*** The proposal of SSSC may bridge a research gap in somatisation disorder,providing researchers with a publicly accessible speech *** addition,the results of the benchmark could show the scientific validity and feasibility of computer audition for speech recognition in somatization disorders.

关键词： Somatisation disorder Machine learning Healthcare Computer audition

Induction System for a Fusion Reactor: Quantum Mechanics Chained up

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Journal of High Energy Physics, Gravitation and Cosmology 2024年第1期10卷 158-166页

作者： Friedrich Björn Grimm CEO of RES-Institute Stuttgart Germany

In the quest for a sustainable and abundant energy source, nuclear fusion technology stands as a beacon of hope. This study introduces a groundbreaking quantum mechanically effective induction system designed for magnetic plasma confinement within fusion reactors. The pursuit of clean energy, essential to combat climate change, hinges on the ability to harness nuclear fusion efficiently. Traditional approaches have faced challenges in plasma stability and energy efficiency. The novel induction system presented here not only addresses these issues but also transforms fusion reactors into integrated construction systems. This innovation promises compact fusion reactors, marking a significant step toward a clean and limitless energy future, free from the constraints of traditional power sources. This revolutionary quantum induction system redefines plasma confinement in fusion reactors, unlocking clean, compact, and efficient energy production.

关键词： Fusion Reactor Plasma Confinement Quantum Mechanics Clean Energy

Conventional Geothermal Systems and Unconventional Geothermal Developments: An Overview

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Open Journal of Geology 2024年第2期14卷 196-246页

作者： Maryam Khodayar Sveinbjörn Björnsson Consultant and Researcher in Geosciences Reykjavík Iceland Formerly at National Energy Authority of Iceland Reykjavík Iceland

This paper provides an overview of conventional geothermal systems and unconventional geothermal developments as a common reference is needed for discussions between energy professionals. Conventional geothermal systems have the heat, permeability and fluid, requiring only drilling down to °C, normal heat flow or decaying radiogenic granite as heat sources, and used in district heating. Medium-temperature (MT) 100°C - 190°C, and high-temperature (HT) 190°C - 374°C resources are mostly at plate boundaries, with volcanic intrusive heat source, used mostly for electricity generation. Single well capacities are °C - 500°C) and a range of depths (1 m to 20 Km), but lack permeability or fluid, thus requiring stimulations for heat extraction by conduction. HVAC is 1 - 2 m deep and shallow geothermal down to 500 m in wells, both capturing °C, with °C are either advanced by geothermal developers at rnatives are still experimental, overcoming costs and technological challenges to become fully commercial. Meanwhile, the conventional geothermal resources remain the most proven opportunities for investments and development.

关键词： Conventional Geothermal Systems Unconventional Geothermal Developments Shallow and Deep Closed-Loops Enhanced Geothermal Systems Supercritical and Millimeter-Wave Drilling

Adaptive State-Dependent Diffusion for Derivative-Free Optimization

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Communications on Applied Mathematics and Computation 2024年第2期6卷 1241-1269页

作者： Bjorn Engquist Kui Ren Yunan Yang Department of Mathematics and the Oden Institute The University of TexasAustinTX 78712USA Department of Applied Physics and Applied Mathematics Columbia UniversityNew YorkNY10027USA Department of Mathematics Cornell UniversityIthacaNY 14853USA

This paper develops and analyzes a stochastic derivative-free optimization strategy.A key feature is the state-dependent adaptive *** prove global convergence in probability with algebraic rate and give the quantitative results in numerical examples.A striking fact is that convergence is achieved without explicit information of the gradient and even without comparing different objective function values as in established methods such as the simplex method and simulated *** can otherwise be compared to annealing with state-dependent temperature.

关键词： Derivative-free optimization Global optimization Adaptive diffusion Stationary distribution Fokker-Planck theory