bluuebunny/crossref_metadata_2025_split huggingface dataset:
T-type multilevel inverter-fed interior PM machine drives based on the voltage regulation feedback and the model predictive control
Authors: Mohamed Essam E. M. , Saeed Mahmoud S. R. 
Published: November 2023

AbstractThe tracking of optimal current trajectories in an interior permanent magnet (IPM) synchronous machine is traditionally realized by a complex online tracking, inaccurate analytical equations, or tiresome offline calibration methods. This paper proposes a modified hybrid feed-forward/feedback flux-weakening algorithm for IPM synchronous machines. In this paper, the utilized power converter is a standard T-type multilevel inverter, and hence, the voltage and current harmonics contents of the conventional two-level inverter are improved. The control algorithm utilizes the optimal current profile for maximum torque per ampere (MTPA) operation and a voltage regulation (VR) feedback control for efficient flux-weakening operation. For infinite-speed IPM machine drives, the d-q current components are limited to follow the maximum torque per voltage (MTPV) trajectory. A low-complexity model predictive control (MPC) is employed to minimize the conflict that arises from using cascaded PI control loops for current and speed control. The performance of the drive is investigated based on the Prius 2004 IPM parameters. Extensive simulation scenarios were performed using the MATLAB/SIMULINK which validates the effectiveness of the proposed algorithm. Real-time simulations based on the dSPACE DS 1103 platform are conducted to confirm the system validity for real hardware implementation. The proposed IPM drive system proves simple structure, fast response, and low harmonic contents.
Impact of real-life use of artificial intelligence as support for human reading in a population-based breast cancer screening program with mammography and tomosynthesis
Authors: Elías-Cabot Esperanza , Romero-Martín Sara , Raya-Povedano José Luis , Brehl A.-K. , Álvarez-Benito Marina 
Published: November 2023

Abstract
Objectives
To evaluate the impact of using an artificial intelligence (AI) system as support for human double reading in a real-life scenario of a breast cancer screening program with digital mammography (DM) or digital breast tomosynthesis (DBT).

Material and methods
We analyzed the performance of double reading screening with mammography and tomosynthesis after implementarion of AI as decision support. The study group consisted of a consecutive cohort of 1 year screening between March 2021 and March 2022 where double reading was performed with concurrent AI support that automatically detects and highlights lesions suspicious of breast cancer in mammography and tomosynthesis. Screening performance was measured as cancer detection rate (CDR), recall rate (RR), and positive predictive value (PPV) of recalls. Performance in the study group was compared using a McNemar test to a control group that included a screening cohort of the same size, recorded just prior to the implementation of AI.

Results
A total of 11,998 women (mean age 57.59 years ± 5.8 [sd]) were included in the study group (5049 DM and 6949 DBT). Comparing global results (including DM and DBT) of double reading with vs. without AI support, we observed an increase in CDR, PPV, and RR by 3.2/‰ (5.8 vs. 9; p < 0.001), 4% (10.6 vs. 14.6; p < 0.001), and 0.7% (5.4 vs. 6.1; p < 0.001) respectively.

Conclusion
AI used as support for human double reading in a real-life breast cancer screening program with DM and DBT increases CDR and PPV of the recalled women.

Clinical relevance statement
Artificial intelligence as support for human double reading improves accuracy in a real-life breast cancer screening program both in digital mammography and digital breast tomosynthesis.

Key Points
• AI systems based on deep learning technology offer potential for improving breast cancer screening programs.
• Using artificial intelligence as support for reading improves radiologists’ performance in breast cancer screening programs with mammography or tomosynthesis.
• Artificial intelligence used concurrently with human reading in clinical screening practice increases breast cancer detection rate and positive predictive value of the recalled women.
Computational study of a microwave plasma reactor based on the TM112 mode for diamond deposition
Authors: Orozco E. A. , Tsygankov P. , Barragan Y. F. , Hernández J. A. , Martinez-Amariz A. , Parada F. F. 
Published: November 2023

AbstractOne of the main features of microwave plasma reactors is the electric field structure in the resonant cavity, which must be both intense and uniform in front of the substrate. For this reason, transverse magnetic modes are often used, especially axisymmetric modes because they produce an axisymmetric plasma. Microwave plasma reactors can be differentiated according to the chosen mode, because this has a direct influence on the diamond film growth process, among other features such as the coupling technique and the used quartz window. Another attractive characteristic of said reactors is obtaining large activation areas of the plasma. In this paper, we propose a microwave plasma reactor based on the TM112 cylindrical mode, which is subject to a computational study. Unlike axisymmetric modes, which activate the plasma on the cavity axis, the TM112 cylindrical mode presents two activation plasma areas. The reactor was designed following the methodology described by Silva et al., and using the Plasma, Radiofrequency (RF), and Heat transfer modules of the software COMSOL Multiphysics. The obtained results are presented in two stages. The first one is related to the initial electric field distribution of the TM112 mode. Next, the generation of the hydrogen plasma was simulated from the interaction of H2 gas with the TM112 microwave field. The plasma activation process is described in detail from graphics of the time evolution of the electron density, hydrogen density, and their respective temperatures until a steady state is reached. Additionally, the influence of the pressure on the concentration and the temperature of both electrons and gas in a steady state is analyzed. The presented results can be useful for the design of plasma reactors for diamond deposition.
Hemodynamic changes in the temporalis and masseter muscles during acute stress in healthy humans
Authors: Rashid Anas , Roatta Silvestro 
Published: November 2023

Abstract
Purpose
Autonomic control of orofacial areas is an integral part of the stress response, controlling functions such as pupil dilatation, salivation, and skin blood flow. However, the specific control of blood flow in head muscles during stress is unknown. This study aims to investigate the hemodynamic response of temporalis and masseter muscles in response to five different stressors.

Methods
Sixteen healthy individuals were subjected to a randomized series of stressors, including cold pressor test, mental arithmetic test, apnea, isometric handgrip, and post-handgrip muscle ischemia, while in the sitting posture. Finger-pulse photoplethysmography was used to measure arterial blood pressure, heart rate, and cardiac output. Near-infrared spectroscopy was used to measure changes in tissue oxygenation and hemoglobin indices from the temporalis and masseter muscles.

Results
All stressors effectively and significantly increased arterial blood pressure. Tissue oxygenation index significantly increased in both investigated head muscles during mental arithmetic test (temporalis: 4.22 ± 3.52%; masseter: 3.43 ± 3.63%) and isometric handgrip (temporalis: 3.45 ± 3.09%; masseter: 3.26 ± 3.07%), suggesting increased muscle blood flow. Neither the masseter nor the temporalis muscles evidenced a vasoconstrictive response to any of the stressors tested.

Conclusion
In the different conditions, temporalis and masseter muscles exhibited similar hemodynamic patterns of response, which do not include the marked vasoconstriction generally observed in limb muscles. The peculiar sympathetic control of head muscles is possibly related to the involvement of these muscles in aggressive/defensive reactions and/or to their unfavorable position with regard to hydrostatic blood levels.
Predictors of cancer patients' utilization of psychooncological support: Examining patient´s attitude and physician´s recommendation
Authors: Goerling Ute , Albus Christian , Bergelt Corinna , Erim Yesim , Faller Hermann , Geiser Franziska , Hönig Klaus , Hornemann Beate , Maatouk Imad , Stein Barbara , Teufel Martin , Wickert Martin , Weis Joachim 
Published: November 2023

Abstract
Purpose
Patients with cancer suffer from a wide range of psychological distress. Nevertheless, in the literature low utilization rates of psychooncological services are reported. Various factors may influence the utilization of professional support during inpatient care. Up to now it is unclear to what extent patients’ attitude towards psychooncological support and physicians’ recommendation for psychooncological care may influence the utilization.

Methods
In a multicenter longitudinal observational study in Comprehensive Cancer Centers Germany, 1398 patients with mixed cancer diagnoses were assessed at baseline during their hospital stay with respect to psychooncological distress and the need for and use of psychooncological services.

Results
Psychooncological support was used by almost 28.4% of patients up to this time. A positive attitude towards psychooncological support was reported by 41.6%. A recommendation of psychooncological support by a physician was received by 16.2%. These patients reported a significant higher level of distress compared to patients who did not received a recommendation. Multivariable logistic regression detected that the utilization rate was 3.79 times higher among patients with positive attitude towards psychooncological support (OR, 3.79; 95% CI 2.51–5.73, p < 0.001). Utilization was 4.21 times more likely among patients who received a physician´s recommendation (OR, 4.21; 95% CI 2.98–5.95, p < 0.001).

Conclusion
The results of the study provide evidence of the relevance of giving more attention to psychooncological distress and attitudes towards psychooncological care. To reduce reservations, patients need low-threshold information about the psychooncological services offered.
Simulating phenomena with exponentiated trigonometric distributions: a comparative study of estimation methods and real-world applications
Authors: Hassanein W. A. , Elhaddad T. A. 
Published: November 2023

AbstractRecent research has highlighted the statistical significance and usefulness of trigonometric distribution models for simulating a variety of phenomena. A new set of distributions generated by exponentiated cosine and tangent functions has been introduced. Consequently, two families of distributions called the exponentiated cosine and tan Stacy distributions are derived. Some vital statistical and reliability characteristics are studied. The finite sample characteristics of parameter estimations are compared to the exponentiated cosine and tan distribution generated by four estimation methods: maximum likelihood, ordinary least squares, weighted least squares, and Cramer–von Mises. The methodologies are evaluated using simulation studies. Finally, the practical applications of the proposed trigonometric versions of the Stacy model are examined and applied on two lifetime reliability engineering datasets and another lifetime medical dataset concerning bladder cancer data. These real applications serve to highlight the effectiveness and adaptability of this innovative families within the respective fields compared with other lifetime well-known distribution models.
AutoML in heavily constrained applications
Authors: Neutatz Felix , Lindauer Marius , Abedjan Ziawasch 
Published: November 2023

AbstractOptimizing a machine learning pipeline for a task at hand requires careful configuration of various hyperparameters, typically supported by an AutoML system that optimizes the hyperparameters for the given training dataset. Yet, depending on the AutoML system’s own second-order meta-configuration, the performance of the AutoML process can vary significantly. Current AutoML systems cannot automatically adapt their own configuration to a specific use case. Further, they cannot compile user-defined application constraints on the effectiveness and efficiency of the pipeline and its generation. In this paper, we proposeCaml, which uses meta-learning to automatically adapt its own AutoML parameters, such as the search strategy, the validation strategy, and the search space, for a task at hand. The dynamic AutoML strategy ofCamltakes user-defined constraints into account and obtains constraint-satisfying pipelines with high predictive performance.
Optimal reinsurance via BSDEs in a partially observable model with jump clusters
Authors: Brachetta Matteo , Callegaro Giorgia , Ceci Claudia , Sgarra Carlo 
Published: November 2023

AbstractWe investigate an optimal reinsurance problem when the loss process exhibits jump clustering features and the insurance company has restricted information about the loss process. We maximise expected exponential utility of terminal wealth and show that an optimal strategy exists. By exploiting both the Kushner–Stratonovich and Zakai approaches, we provide the equation governing the dynamics of the (infinite-dimensional) filter and characterise the solution of the stochastic optimisation problem in terms of a BSDE, for which we prove existence and uniqueness of a solution. After discussing the optimal strategy for a general reinsurance premium, we provide more explicit results in some relevant cases.
Correlates and trajectories of relapses in relapsing–remitting multiple sclerosis
Authors: Young Carolyn A. , Rog David J. , Sharrack Basil , Tanasescu Radu , Kalra Seema , Harrower Timothy , Tennant Alan , Mills Roger J. ,   on behalf of the Trajectories of Outcome in Neurological Conditions-MS Study Group, Young Carolyn , Rog David , Sharrack Basil , Constantinescu Cris , Kalra Seema , Majeed Tahir , Santander Helen , Harrower Tim , Leach Oliver , Nicholas Richard , Ford Helen , Woolmore John , Kipps Chris , Johnston Clare , Thorpe John , Paling David , Falah Yasser , Ellis Cathy , Pinto Ashwin , Hanemann C. Oliver , Chandran Siddharthan , Malaspina Andrea , Kitley Jo , Palace Jacqueline , Fuller Tracy , Mottram Pat , Terrett Helen , Scalfari Antonio 
Published: November 2023

Abstract
Background and aims
In people with relapsing–remitting multiple sclerosis (pwRRMS), data from studies on non-pharmacological factors which may influence relapse risk, other than age, are inconsistent. There is a reduced risk of relapses with increasing age, but little is known about other trajectories in real-world MS care.

Methods
We studied longitudinal questionnaire data from 3885 pwRRMS, covering smoking, comorbidities, disease-modifying therapy (DMT), and patient-reported outcome measures, as well as relapses during the past year. We undertook Rasch analysis, group-based trajectory modelling, and multilevel negative binomial regression.

Results
The regression cohort of 6285 data sets from pwRRMS over time showed that being a current smoker was associated with 43.9% greater relapse risk; having 3 or more comorbidities increased risk and increasing age reduced risk. Those diagnosed within the last 2 years showed two distinct trajectories, both reducing in relapse frequency but 25.8% started with a higher rate and took 4 years to reduce to the rate of the second group. In the cohort with at least three data points completed, there were three groups: 73.7% followed a low stable relapse rate, 21.6% started from a higher rate and decreased, and 4.7% had an increasing then decreasing pattern. These different trajectory groups showed significant differences in fatigue, neuropathic pain, disability, health status, quality of life, self-efficacy, and DMT use.

Conclusions
These results provide additional evidence for supporting pwRRMS to stop smoking and underline the importance of timely DMT decisions and treatment initiation soon after diagnosis with RRMS.
Olympus: a GDPR compliant blockchain system
Authors: Gonçalves Ricardo Martins , da Silva Miguel Mira , da Cunha Paulo Rupino 
Published: November 2023

AbstractBlockchain has been gaining significant interest in several domains. However, this technology also raises relevant challenges, namely in terms of data protection. After the General Data Protection Regulation (GDPR) has been published by the European Union, companies worldwide changed the way they process personal data. This project provides a model and implementation of a blockchain system to store personal data complying with GDPR. We examine the advantages and challenges and evaluate the system. We use Hyperledger Fabric as blockchain, Interplanetary File System to store personal data off-chain, and a Django REST API to interact with both the blockchain and the distributed file system. Olympus has three possible types of users: Data Subjects, Data Processors and Data Controllers and a fourth participant, Supervisor Authority, that, despite not being an explicit role, can perform all verifications that GDPR mandates. We conclude that it is possible to create a system that overcomes the major challenges of storing personal data in a blockchain (Right to be Forgotten and Right to Rectification), while maintaining its desirable characteristics (auditability, verifiability, tamper resistance, distributed—remove single points of failure) and complying with GDPR.
Simulating glacier lake outburst floods (GLOFs) with a two-phase/layer debris flow model considering fluid-solid flow transitions
Authors: Meyrat G. , Munch J. , Cicoira A. , McArdell B. , Müller C. R. , Frey H. , Bartelt P. 
Published: November 2023

AbstractGlacier lake outburst floods (GLOFs) initiate with the rapid outburst of a glacier lake, endangering downstream populations, land, and infrastructure. The flow initiates as a mud flow; however, with the entrainment of additional solid material, the flood will often transform into a debris flow. As the run-out slope flattens, the coarse solid material deposits and the flow de-waters. The flow transforms back into a muddy, hyperconcentrated flow of fine sediments in suspension. These flow transitions change the flow composition dramatically and influence both the overall mass balance and flow rheology of the event. In this paper, we apply a two-phase/layer model to simulate flow transitions, solid–fluid phase separations, entrainment, and run-out distances of glacier lake outburst floods. A key feature of the model is the calculation of dilatant actions in the solid–fluid mixture which control flow transitions and phase separations. Given their high initial amount of fluid within the flow, GLOFs are sensitive to slope changes inducing flow transitions, which also implies changes in the flow rheology. The changes in the rheology are computed as a function of the flow composition and do not need any adaptation by ad-hoc selection of friction coefficients. This procedure allows the application of constant rheological input parameters from initiation to run-out. Our goal is to increase the prediction reliability of debris flow modeling. We highlight the problems associated with initial and boundary (entrainment) conditions. We test the new model against the well-known Lake 513 (Peru, 2010), Lake Palcacocha (Peru, 1941), and Lake Uchitel in the Aksay Valley (Kyrgyzstan) GLOF events. We show that flow transition modeling is essential when studying areas that have significant variations in slope.
Shake table testing of a half-scale stone masonry building aggregate
Authors: Tomić I. , Penna A. , DeJong M. , Butenweg C. , Correia A. A. , Candeias P. X. , Senaldi I. , Guerrini G. , Malomo D. , Beyer K. 
Published: November 2023

AbstractMasonry aggregates have developed throughout city centres of Europe due to a centuries-long densification process that generally lacked consistent planning or engineering. Adjacent units are connected either through interlocking stones or a layer of mortar. Without interlocking stones, the connection between the units is weak, and an out of-phase response of the units can lead to separation and pounding. Modelling guidelines and code instructions are missing for modelling the interaction of such adjacent units because of scarce experimental data. Therefore, in this study an unreinforced stone masonry aggregate was tested on the bidirectional shake table with an incremental seismic protocol as a part of the SERA AIMS—Adjacent Interacting Masonry Structures project. The aggregate was constructed at half-scale with double-leaf undressed stone masonry without interlocking between the units. Floors were built with timber beams and one layer of planks, with different beam span orientation for each unit. After significant damage, one of the units was retrofitted by anchoring the timber beams to the walls to prevent out-of-plane failure and testing was continued. Significant interaction between the units was observed with specific damage mechanisms. Cracking and separation were observed at the interface in both longitudinal and transverse direction, starting at lower intensity runs and progressively increasing. Bidirectional seismic excitation affected the unit separation, with friction forces seemingly playing a role in the transverse direction. Signs of pounding at the interface were observed during higher intensity runs, together with the formation of a soft storey mechanism at the upper storey of the higher unit. The mechanism involved an out-of-plane response of the shared wall, with a horizontal crack at the height of the interaction. These findings contribute to a better understanding of the seismic behaviour of masonry aggregates.
Germination responses with different treatments, seed vigour and seedling growth of Pterolobium stellatum (Forssk.) provenances stored from 19 to 30 years
Authors: Alem Shiferaw , Habrová Hana , Houšková Kateřina 
Published: November 2023

AbstractKnowledge of the genetic variability of different species for conservation purposes and quality seedling production after longer storage time is important. The aim of the research paper was to examine the effect of longer seed storage periods (19–30 year) on seed viability, seed vigour and initial growth of seedlings from five provenances of Pterolobium stellatum (Forssk). Seeds collected from Dabena, Gambo, Agaro, Bishofitu, and Merti localities and stored for 19, 19, 21, 25, and 30 years, respectively used for the study. Different seed dormancy-breaking treatments such as; soaking in cold water for 48 h (CW-48); soaking in hot water for 10 min (HW-10); 20 min (HW-20) and mechanical scarification; i.e., nicking (NK) used for the germination of the seeds. A randomized complete block design was used for the experiment and the study undertaken in a greenhouse. For each treatment, four replications and for each replication, 50 seeds were used. One-way analysis of variance was used for germination index, early seedling growth and seed vigour index data. The results showed that for all the provenance seeds stored for different periods, NK treatment resulted relatively in a higher mean germination percentage and germination indices as compared to the other pre-treatments. The seed vigour index result showed significant differences among the different provenances (P < 0.001). Similarly, there were significant differences among the early growth of seedlings germinated from different provenance seeds (P < 0.001). The seeds collected from Merti provenance and stored for 30 years and Dabena provenance, stored for 19 years, have relatively resulted in higher mean germination index, seed vigour and seedling growth relative to the other studied provenance seeds. We observed that provenance had a more significant influence on germination, seed vigour and seedling growth than the seed storage period for the P. stellatum. Finally it is recommended that despite there is inter population variation, the seeds of P. stellatum can be stored for a longer time and application of nicking as a dormancy breaking treatment could enhance seed germination of the species.