bluuebunny/crossref_metadata_2025_split huggingface dataset:
Flexible open network operating system architecture for implementing higher scalability using disaggregated software‐defined optical networking
Authors: Nsafoa‐Yeboah Kenneth , Tchao Eric Tutu , Kommey Benjamin , Agbemenu Andrew Selasi , Klogo Griffith Selorm , Akrasi‐Mensah Nana Kwadwo 
Published: December 2023

AbstractThe enhanced capacity of optical networks is a significant advantage within the global telecommunications industry. Optical networks provides transmission of information over large distances with reduced latency. However, the growing intricacy of network topologies poses a significant challenge to network adaptability, network resilience, device compatibility, and service quality in the contemporary era of technology and 5G networks. In light of these challenges, recent studies leverages on disaggregation in the context of Software Defined Network (SDN) and network service orchestrators as a viable remedy. Disaggregated optical systems offer SDON (Software‐Defined Optical Networking) enhanced control options and third‐party dynamism streamlining upgrades and diminishing single vendor dependency. Although, the advancement of disaggregation improves network flexibility and vendor neutrality of Software Defined Optical Networking (SDON), this improvement comes at the cost of reduced scalability and network controllability performance. The current research paper posits two potential resolutions to the aforementioned challenge. The authors present recommendations and an enhanced architecture that leverages Open Network Operating System (ONOS) containers and Kubernetes orchestration to improve scalability inside the Software‐Defined Optical Networking (SDON) architecture. The suggested architectural design has underlining novel flow charts and algorithms that enhances scalability performance by 33% while also preserving flexibility and controllability in comparison to pre‐existing SDON architectures. This architecture also makes use of the Mininet‐Optical physical‐layer architecture to simulate a real‐time scenario, as well as yang models from the Open Disaggregated Transport Network (ODTN) working group, the pioneers of SDONs. A detailed analysis of the rules and procedural processes involved in the implementation of the proposed architecture. In order to demonstrate the practical application of this architectural framework to a real‐world Software‐Defined Optical Network (SDON) system, the pre‐existing SDON ONOS architecture within the Optical Transport Domain Networking (OTDN) working group was adjusted and refined. This adaptation aimed to illustrate the use of ONOS in conjunction with established optical network systems, highlighting the advantages it offers.
Immediate Partial Breast and Nipple–Areola Complex Reconstruction Using a Superficial Circumflex Iliac Artery Perforator Flap
Authors: Pons Gemma , Sisternas Lucía , Masià Jaume 
Published: December 2023

AbstractThe superficial circumflex iliac artery perforator (SCIP) flap is a versatile flap that has been described for various applications, mostly for lower extremity coverage and head and neck reconstructions. However, there are few publications reporting its use for breast reconstruction, mainly because of its low volume availability. In this article, we present the case of a patient who successfully underwent a partial breast and immediate nipple–areola complex (NAC) reconstruction with an SCIP flap. She had been previously reconstructed with an implant after a nipple-sparing mastectomy, but the NAC turned out to be involved with cancer needing further resection. Our goal with this article, is to introduce a novel concept for addressing partial breast and NAC reconstruction and mostly, to illustrate the importance of an adaptable surgical plan based on every individual case emphasizing the versality of microsurgery for breast cancer reconstruction.
Painful Unilateral Knee Snapping after Hyperextension Injury and Meniscus Tear
Authors: Karsen Phillip , Brinkman Joseph , Day Jonathan , McGurren Daniel , Patel Karan 
Published: December 2023

AbstractThis case involves a healthy male with painful lateral knee pain and snapping after a hyperextension injury. Initially, this was felt to be from a displaced lateral meniscus tear; however, he failed to improve after meniscal debridement. Further workup with an ultrasound and magnetic resonance imaging identified an aberrant biceps femoris anatomy. He was taken to the operating room and the aberrant slip was identified. A tenodesis of the aberrant slip to the biceps femoris was completed. This resolved the patient's pain and snapping, and he was able to return to all activities.
Evolutionary game analysis on decision-making behaviors of participants in mega projects
Authors: Chen Daoping , Chen Binbin 
Published: December 2023

AbstractMega projects have a huge impact on the economy and society. Preventing collusive behavior and introducing public participation in supervision are conducive to the governance of mega projects and are crucial to the success of mega projects. The owner, the construction party, and the supervisor of the mega project are regarded as a collusion-body that may collude. Based on the evolutionary game theory, an evolutionary game model with collusion-body, the government, and the public as the participants is constructed. The stability of each participant’s strategy selection is analyzed, the conditions for achieving the evolutionarily stable strategy are obtained, and the evolutionary path of the strategy is simulated. The results show that the costs and benefits have important effects on the behavior of the three participants. Each participant’s strategy choice is affected by other participants, and there is a certain critical probability for each participant. If the critical value is greater than or less than, the participant’s strategy will change. There are five evolutionary stable strategies in the game system, and the costs and benefits conditions to achieve each evolutionary stable strategy are different. In the case of active government intervention and public participation in supervision, the ideal stabilization strategy can be achieved by changing the costs and benefits parameters of the participants, and then the governance effectiveness of the collusive behavior of mega projects can be improved.
How smart city building improved corporate performance: empirical evidence of China’s a-share listed companies
Authors: Jiang Xiaoli , Han Xue , Xue Li , Yu Zhuo , Wei Shuo , Xu Hejun 
Published: December 2023

AbstractSmart city construction is crucial for regional economic development, and the micro-level impact of such construction on business operations cannot be ignored. Based on the panel data of Shanghai and Shenzhen A-share listed companies from 2008 to 2020, this paper investigates the relationship between smart city construction and firm performance and its mechanism of action. The study findings show that (1) smart city construction significantly improves enterprise performance; (2) the improvements are significant across all industries and regions; and (3) the impact of smart city construction on small and medium-sized enterprises (SMEs) and nonstate enterprises is more significant than that on large enterprises and state-owned enterprises. These findings provide a theoretical framework and fresh perspectives for encouraging coordinated regional development and new urbanization construction.
Framing the path to net zero
Authors: Fuoli Matteo , Beelitz Annika 
Published: December 2023

Abstract
Big corporations are a leading contributor to global carbon emissions and their investment decisions have a
significant impact on the world’s ability to tackle climate change. This study combines corpus and discourse approaches to examine
how major corporate emitters have responded to the Paris Agreement, how they legitimize their practices amid mounting public
pressure, and how companies operating in high- and middle-income countries differ in their framing of climate change. The results
show that carbon majors place increasing focus on climate issues, widely support the goals of the Paris Agreement, and are
increasingly making net-zero pledges. However, close inspection of linguistic patterns reveals a troubling disconnect between
proclaimed goals, the solutions advocated for, and the radical steps needed to address the escalating climate crisis. Companies
from middle-income countries devote comparatively less attention to climate change, which points to the need for better
coordinated global efforts to address this problem.
Do they think that joy and misery are temporary? Comparing trajectories of current and predicted life satisfaction across life events
Authors: Hudde Ansgar 
Published: December 2023

ABSTRACT
When people marry or have their first baby, their life satisfaction spikes but fades soon thereafter. Similarly, when people separate from a partner or become widowed, their satisfaction decreases but largely recovers within a few years. I analyse to what degree people who experience these life events expect that their current shift towards joy or misery is temporary vs. long-lasting. Data are from the German Socio-Economic Panel (SOEP) and are analysed with a novel estimation strategy that uses month-specific information on the timing of interviews and life events. I compare trajectories of people's current life satisfaction and anticipated life satisfaction, i.e. the level of satisfaction they expect to have five years into the future. Results show that people expect some of these life events’ joy or misery to stay, but the majority to fade. These findings reveal that, to a substantial degree, people are able to see their situation from a distance and separate their current feelings from their long-term life prospects. This may contribute to people's overall well-being and sustainable life strategies.
The charge and mass symmetry breaking in the KK
K¯
system
Authors: Filikhin I , Kezerashvili R Ya , Vlahovic B 
Published: December 2023

Abstract
In the framework of the Faddeev equations in configuration space, we investigate the K(1460) meson as a resonant state of the

KK

K

¯

kaonic system. We perform calculations for the particle configurations K
0
K
+
K
− and

K

0

K

+

K

0

¯

within two models: the ABC model, in which all three particles are distinguishable, and the AAC model when two particles are identical. The models differ in their treatment of the kaon mass difference and the attractive Coulomb force between the K
+
K
− pair. We found that the Coulomb shift adds over 1 MeV to the three-body binding energy. The expected correction to the binding energy due to mass redistribution from AA to AB is found to be negligible, up to a maximum of 6% of the relative mass correction. At the same time, the symmetry of the wave function is distorted depending on the mass ratio value. We found that the repulsive KK interaction plays an essential role in the binding energy of the

KK

K

¯

system and reports the mass of 1461.8 or 1464.1 MeV for the neutral K
0(1460) and 1466.5 or 1468.8 MeV for the charged K
+(1460) resonances, respectively, depending on the parameter sets for KK and

K

K

¯

interactions.
Vehicle integrated navigation IMU mounting angles estimation method based on nonlinear optimization
Authors: Lin Feifan , Wang Shiliang , Chen Yanping , Zou Mengqiang , Peng Hui , Liu Yu 
Published: December 2023

Abstract
A vehicle integrated navigation system based on Global Navigation Satellite System (GNSS) aided Inertial Navigation System (INS) enhances its navigation accuracy by utilizing non-holonomic constraints and odometer velocity. However, the navigation accuracy of the system is compromised due to the challenges in the estimation of the inertial measurement unit (IMU) mounting angles relative to the host vehicle. This paper presents a method for estimating the IMU mounting angles of a vehicle that integrated navigation system through a nonlinear optimization. The proposed method firstly achieves the initial alignment of the vehicle integrated navigation system through a GNSS/INS loosely coupled algorithm. Then, the vehicle navigation algorithm is switched to the INS algorithm after collecting 100 satellite-fixed solutions. Finally, a nonlinear optimization objective function based on the difference between the satellite-fixed solutions and the INS integration results is constructed to solve for the IMU mounting angles. Experiments were conducted by using a Murata SCHA634 IMU on a land vehicle to validate the proposed method. This method has a reduction of approximately 30% in the three-dimensional positioning accuracy within

1
σ

error compared to that without mounting angles compensation, and a reduction of approximately 15% when compared with the traditional approach of compensating for IMU mounting angles using the error state Kalman filter method.
The most probable transition paths of stochastic dynamical systems: a sufficient and necessary characterisation
Authors: Huang Yuanfei , Huang Qiao , Duan Jinqiao 
Published: December 2023

Abstract
The most probable transition paths (MPTPs) of a stochastic dynamical system are the global minimisers of the Onsager–Machlup action functional and can be described by a necessary but not sufficient condition, the Euler–Lagrange (EL) equation (a second-order differential equation with initial-terminal conditions) from a variational principle. This work is devoted to showing a sufficient and necessary characterisation for the MPTPs of stochastic dynamical systems with Brownian noise. We prove that, under appropriate conditions, the MPTPs are completely determined by a first-order ordinary differential equation. The equivalence is established by showing that the Onsager–Machlup action functional of the original system can be derived from the corresponding Markovian bridge process. For linear stochastic systems and the nonlinear Hongler’s model, the first-order differential equations determining the MPTPs are shown analytically to imply the EL equations of the Onsager–Machlup functional. For general nonlinear systems, the determining first-order differential equations can be approximated, in a short time or for the small noise case. Some numerical experiments are presented to illustrate our results.
QMLS: quaternion mutual learning strategy for multi-modal brain tumor segmentation
Authors: Deng Zhengnan , Huang Guoheng , Yuan Xiaochen , Zhong Guo , Lin Tongxu , Pun Chi-Man , Huang Zhixin , Liang Zhixin 
Published: December 2023

Abstract

Objective. Due to non-invasive imaging and the multimodality of magnetic resonance imaging (MRI) images, MRI-based multi-modal brain tumor segmentation (MBTS) studies have attracted more and more attention in recent years. With the great success of convolutional neural networks in various computer vision tasks, lots of MBTS models have been proposed to address the technical challenges of MBTS. However, the problem of limited data collection usually exists in MBTS tasks, making existing studies typically have difficulty in fully exploring the multi-modal MRI images to mine complementary information among different modalities. Approach. We propose a novel quaternion mutual learning strategy (QMLS), which consists of a voxel-wise lesion knowledge mutual learning mechanism (VLKML mechanism) and a quaternion multi-modal feature learning module (QMFL module). Specifically, the VLKML mechanism allows the networks to converge to a robust minimum so that aggressive data augmentation techniques can be applied to expand the limited data fully. In particular, the quaternion-valued QMFL module treats different modalities as components of quaternions to sufficiently learn complementary information among different modalities on the hypercomplex domain while significantly reducing the number of parameters by about 75%. Main results. Extensive experiments on the dataset BraTS 2020 and BraTS 2019 indicate that QMLS achieves superior results to current popular methods with less computational cost. Significance. We propose a novel algorithm for brain tumor segmentation task that achieves better performance with fewer parameters, which helps the clinical application of automatic brain tumor segmentation.
Machine learning to detect, stage and classify diseases and their symptoms based on inertial sensor data: a mapping review
Authors: Bibbo Daniele , De Marchis Cristiano , Schmid Maurizio , Ranaldi Simone 
Published: December 2023

Abstract
This article presents a systematic review aimed at mapping the literature published in the last decade on the use of machine learning (ML) for clinical decision-making through wearable inertial sensors. The review aims to analyze the trends, perspectives, strengths, and limitations of current literature in integrating ML and inertial measurements for clinical applications. The review process involved defining four research questions and applying four relevance assessment indicators to filter the search results, providing insights into the pathologies studied, technologies and setups used, data processing schemes, ML techniques applied, and their clinical impact. When combined with ML techniques, inertial measurement units (IMUs) have primarily been utilized to detect and classify diseases and their associated motor symptoms. They have also been used to monitor changes in movement patterns associated with the presence, severity, and progression of pathology across a diverse range of clinical conditions. ML models trained with IMU data have shown potential in improving patient care by objectively classifying and predicting motor symptoms, often with a minimally encumbering setup. The findings contribute to understanding the current state of ML integration with wearable inertial sensors in clinical practice and identify future research directions. Despite the widespread adoption of these technologies and techniques in clinical applications, there is still a need to translate them into routine clinical practice. This underscores the importance of fostering a closer collaboration between technological experts and professionals in the medical field.
Early diagnosis of citrus Huanglongbing by Raman spectroscopy and machine learning
Authors: Kong Lili , Liu Tianyuan , Qiu Honglin , Yu Xinna , Wang Xianda , Huang Zhiwei , Huang Meizhen 
Published: December 2023

Abstract
Timely diagnosis of citrus Huanglongbing (HLB) is fundamental to suppressing disease spread and reducing economic losses. This paper explores the combination of Raman spectroscopy and machine learning for on-site, accurate and early diagnosis of citrus HLB. The tissue lesion characteristics of citrus leaves at different stages of HLB infection was explored by Raman spectroscopy, and a scientific spectral acquisition strategy was proposed. Combined with machine learning for feature extraction, modeling learning, and predictive analysis, the diagnostic accuracies of principal component analysis (PCA)-Partial least-square and PCA-support vector machine models for the prediction set were 94.07% and 95.56%, respectively. Compared with conventional random detection method, the detection strategy proposed in this paper shows higher accuracy, especially in early HLB diagnosis with significant advantages.
Proton Energy Spectra From Deuteron Induced Reaction on Copper At 14,5 MeV Deuteron Energy
Authors: Zholdybayev T.K. , Ussabayeva G.A. , Temirzhanov A.A. , Mukan Zh.T. , Sadykov B.M. , Duisebayev B.A. 
Published: December 2023

Abstract
Double differential cross sections have been measured for light-charged particle production in deuteron-induced reactions on
nat
Cu at incident energies of 14.5 MeV. The experiment was performed at the isochronous cyclotron of the Institute of Nuclear Physics (Kazakhstan). Charged particles were detected using a set of Si and CsI detectors from 30° to 135°, by step of 15°. The integral cross-sections were determined by integrating over the angle the double differential cross-sections. Double differential and integral charged particle emission cross-sections have been calculated by the TALYS 1.9 nuclear reaction which code based on a modified version of the exciton model of the pre-equilibrium nuclear decay. Direct, compound, and pre-equilibrium reaction contributions have been determined for the emission of proton particles.
Structural condition of container material long-term used for hydrogen
Authors: Akaev S O , Dikov A S , Larionov A S 
Published: December 2023

Abstract
The paper shows the structural condition of the container wall material, which has been used for a long time under hydrogen storage conditions. The features of the structure are shown depending on the thickness and direction of the wall section. There are signs of deterioration of the structure near the inner surface of the container wall caused by the intense interaction with hydrogen.
Study of the first aquifer on the territory of the former test site “Azgir” to determine potential migration routes of radionuclides
Authors: Severinenko M A , Akhmetzhanova D S , Makarova V A , Krasnopyorova M V , Koshzhanov A T , Matiyenko L D 
Published: December 2023

Abstract
The article presents the results of the study of the hydrogeological situation of the first aquifer of the former test site “Azgir” with the purpose of determining possible ways of radionuclide migration from the underground cavities of the former test site “Azgir” established more than 50 years ago. It was demonstrated that groundwater of the first aquifer lies in the form of separate scattered lenses, as well as a local basin, which has the role of a potential groundwater reservoir. Currently, there are no processes of technogenic radionuclides migration from underground cavities into the first aquifer.
Irradiation device development with changing neutron spectrum
Authors: Nessipbay A Zh , Gizatulin Sh H , Akhanov A M , Kisselyov K S , Aitkulov M T , Shaimerdenov A A , Yoshiharu Nagao 
Published: December 2023

Abstract
This paper presents a sketch drawing of the developed design of an irradiating device, which allows to regulate the neutron energy spectrum in it, as well as the results of neutron-physical calculations with predicted values of the range of neutron flux density variation in different energy groups. It is shown that the fraction of thermal and over-thermal neutrons in the dry irradiation channel increases with increasing beryllium filling packing fraction. While the fraction of fast neutrons (> 1.15 MeV) decreases. In the wet irradiation channel, the dependence of thermal and over-thermal neutrons is similar to that in the dry channel, but the effect is much smaller.
The first findings of the study of the territory of the water basin of the Kapshagai Reservoir. Uranium isotope distribution
Authors: Solodukhin Vladimir P. , Ydyrysheva Saulet K. , Lennik Svetlana G. , Kabirova Gulinur M. 
Published: December 2023

Abstract
This article presents the first results of the examination of environmental objects (water, coastal soil, bottom sediments) of the Kapshagai Reservoir water basin. Radionuclide composition of selected samples by alpha-, gamma spectrometry and total alpha- and beta-activity were determined. It has been established that in some water samples, the total alpha activity exceeds the standard of the Republic of Kazakhstan for drinking water, the total beta activity does not exceed the standard. Presents the results of uranium-238, uranium-234, uranium-235 activities and also gives the ratio of uranium-234 to uranium-238 activities, which is an important indicator of water contamination by this element.