bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptive intensity modulated proton therapy using 4D robust planning: a proof-of-concept for the application of dose mimicking approach
Authors: Kaushik Suryakant , Stützer Kristin , Ödén Jakob , Fredriksson Albin , Toma-Dasu Iuliana 
Published: August 2024

Abstract

Objective. A four-dimensional robust optimisation (4DRO) is usually employed when the tumour respiratory motion needs to be addressed. However, it is computationally demanding, and an automated method is preferable for adaptive planning to avoid manual trial-and-error. This study proposes a 4DRO technique based on dose mimicking for automated adaptive planning. Approach. Initial plans for 4DRO intensity modulated proton therapy were created on an average CT for four patients with clinical target volume (CTV) in the lung, oesophagus, or pancreas, respectively. These plans were robustly optimised using three phases of four-dimensional computed tomography (4DCT) and accounting for setup and density uncertainties. Weekly 4DCTs were used for adaptive replanning, using a constant relative biological effectiveness (cRBE) of 1.1. Two methods were used: (1) template-based adaptive (TA) planning and (2) dose-mimicking-based adaptive (MA) planning. The plans were evaluated using variable RBE (vRBE) weighted doses and biologically consistent dose accumulation (BCDA). Main results. MA and TA plans had comparable CTV coverage except for one patient where the MA plan had a higher D98 and lower D2 but with an increased D2 in few organs at risk (OARs). CTV D98 deviations in non-adaptive plans from the initial plans were up to −7.2 percentage points (p.p.) in individual cases and −1.8 p.p. when using BCDA. For the OARs, MA plans showed a reduced mean dose and D2 compared to the TA plans, with few exceptions. The vRBE-weighted accumulated doses had a mean dose and D2 difference of up to 0.3 Gy and 0.5 Gy, respectively, in the OARs with respect to cRBE-weighted doses. Significance. MA plans indicate better performance in target coverage and OAR dose sparing compared to the TA plans in 4DRO adaptive planning. Moreover, MA method is capable of handling both forms of anatomical variation, namely, changes in density and relative shifts in the position of OARs.
Predicting stroke volume variation using central venous pressure waveform: a deep learning approach
Authors: Park Insun , Park Jae Hyon , Koo Bon-Wook , Kim Jin-Hee , Jeon Young-Tae , Na Hyo-Seok , Oh Ah-Young 
Published: August 2024

Abstract

Objective. This study evaluated the predictive performance of a deep learning approach to predict stroke volume variation (SVV) from central venous pressure (CVP) waveforms. Approach. Long short-term memory (LSTM) and the feed-forward neural network were sequenced to predict SVV using CVP waveforms obtained from the VitalDB database, an open-source registry. The input for the LSTM consisted of 10 s CVP waveforms sampled at 2 s intervals throughout the anesthesia duration. Inputs of the feed-forward network were the outputs of LSTM and demographic data such as age, sex, weight, and height. The final output of the feed-forward network was the SVV. The performance of SVV predicted by the deep learning model was compared to SVV estimated derived from arterial pulse waveform analysis using a commercialized model, EV1000. Main results. The model hyperparameters consisted of 12 memory cells in the LSTM layer and 32 nodes in the hidden layer of the feed-forward network. A total of 224 cases comprising 1717 978 CVP waveforms and EV1000/SVV data were used to construct and test the deep learning models. The concordance correlation coefficient between estimated SVV from the deep learning model were 0.993 (95% confidence interval, 0.992–0.993) for SVV measured by EV1000. Significance. Using a deep learning approach, CVP waveforms can accurately approximate SVV values close to those estimated using commercial arterial pulse waveform analysis.
Historical development of electron swarm physics based on the Boltzmann equation towards in-depth understanding of a low-temperature collisional plasma
Authors: Makabe Toshiaki , Sugawara Hirotake 
Published: August 2024

Abstract
Theoretical study of the electron kinetics (i.e. the velocity distribution and the transport parameter) in gases is generally conducted using the electron Boltzmann equation. The year 2022 marked 150 years since the formulation of the Boltzmann equation. Even in the last several decades, the historical progress has been made synchronously with the development of innovative technologies in gaseous electronics and in combination with the appearance of computers with sufficient speed and memory. Electron kinetic theory based on the Boltzmann equation has mostly been developed as the swarm physics in the hydrodynamic regime in the dc and radio frequency electric fields. In particular, the temporal characteristics are understood in terms of the collisional relaxation times between electron and gas molecule. There are two main theoretical approaches based on the Boltzmann equation for finding the velocity distribution. One is the traditional description of the electron kinetics, starting from the Boltzmann statistics in velocity space under a uniform density or a small density gradient of electrons. The other most recent approach is based on the phase-space tracking of the velocity distribution where the electron transport parameter is given by the moment of the electron density distribution in position space. In the present paper, we will explore the historical development of the electron Boltzmann equation with respect to three key items: collision term, solution method, and intrinsic electron transport in a hydrodynamic regime involved as the key elements in the low-temperature collisional plasma. The important topics listed in a table are briefly noted and discussed.
Soliton solutions of cubic quintic septimal nonlinear Schrödinger wave equation with conformable derivative by two distinct algorithms
Authors: Murad Muhammad Amin S 
Published: August 2024

Abstract
This paper investigates the cubic-quintic-septimal nonlinear Schrödinger wave equation with a conformable derivative, which governs the evolution of light beams in a weak nonlocal medium. The analysis utilizes the Kudryashov method and the enhanced modified tanh expansion method. By utilizing these analytical integration schemes, various optical wave solutions are derived within the present conformable model. The paper demonstrates the significance of these optical soliton solutions by illustrating different soliton solutions, including kink-type, bell-shaped, singular, dark, and wave soliton solutions, depicted via contour, three-dimensional, and two-dimensional representations. Moreover, it is crucial to emphasize the importance of analyzing the cubic-quintic-septimal nonlinear Schrödinger wave equation, which finds utility across a spectrum of fields including optics, quantum mechanics, and the study of nonlinear wave propagation. Moving forward, these approaches hold promise for investigating diverse sets of differential equations within multiple domains of applied sciences. This governing equation also has numerous applications in nonlinear optics, such as describing the propagation of laser beams through materials with nonlinear optical properties. The inclusion of these nonlinearities illustrates the interaction and behavior of light beams in weakly non-local media.
Cosmological wormhole: an analytical description
Authors: Chakraborty Subenoy , Chakraborty Madhukrishna 
Published: August 2024

Abstract
An attempt has been made to have an analytical description for possible traversable wormhole in non-static spherically symmetric space-time supported by anisotropic fluid. Both trivial and non-trivial choices of the red-shift function result in identical WH configuration and it is possible to have emergent scenario for evolution of the background space-time in both the cases.
Time-series bidirectional adjustable N-soft expert MABAC method and its application for multi-attribute group decision-making
Authors: Chen Yanan , Zhou Xiaoguang 
Published: August 2024

Abstract
In hybrid models of soft expert sets, experts express only agreed or disagreed opinions about existing grades. This paper proposes a time-series bidirectional adjustable N-soft expert set model to address the shortcomings of existing models that cannot adjust existing grades to a more reasonable state or describe decision problems involving different times. Firstly, this model can explain the experts’ uncertain opinions and make positive or negative adjustments about existing grades. Secondly, the model contains information about time, describes dynamic multi-attribute group decision-making problems and explores objects’ changes and developments over time. And some related operations and propositions are derived. In addition, a new method called the bidirectional adjustable N-soft expert MABAC (multi-attributive border approximation area comparison) is proposed. On the one hand, the proposed method uses deviation maximizing and exponential decay methods to determine the time weights, ensuring the reliability of the time weights. On the other hand, it ranks objects based on their distances from an approximate boundary region, limiting the unconditional compensation among attribute values. Finally, this paper presents an example to verify its effectiveness and reliability by results analysis, sensitivity analysis, and comparison analysis.
Friction stir welding of AA2024-T3 and SS304 alloys: microstructural analysis, microhardness evaluation, and tensile performance
Authors: Mir Fayaz Ahmad , Khan Noor Zaman , Mukhtar Zahid , Badruddin Irfan Anjum , Kamangar Sarfaraz , Nisar Lubaid 
Published: August 2024

Abstract
This study examines the feasibility of friction stir welding (FSW) for dissimilar butt joints formed between 3 mm thick 2024-T3 aluminum alloy and AISI 304 stainless steel. It explores the impact of operational parameters, particularly traverse speeds of 20 and 40 mm min−1, a fixed tool rotation speed of 450 rpm, a tool pin offset of 1.5 mm, and a tool shoulder diameter of 18 mm, on microstructure, microhardness, and tensile strength. A traverse speed of 40 mm min−1 resulted in a lower peak temperature of 257.75 °C, while optimal conditions at a speed of 20 mm min−1 led to peak temperatures of 356.5 °C. This higher temperature facilitated material deformation, improved flow, enhanced mixing, and contributed to grain refinement, with an average grain size of 4.2 μm. Vickers microhardness tests revealed a maximum hardness of 339 Hv at a traverse speed of 40 mm min−1 and 413 Hv at 20 mm min−1. The ultimate tensile strength (UTS) reached 338 MPa, resulting in a joint efficiency (JE %) of 76.81% for the weld performed at optimal conditions.
Floquet engineering of a dynamical Z2 lattice gauge field with ultracold atoms
Authors: Sun 孙 Xiangxiang 祥祥 , Qi 齐 Hao-Yue 浩月 , Zhang 张 Pengfei 鹏飞 , Zheng 郑 Wei 炜 
Published: August 2024

Abstract
Gauge field theory is a fundamental concept in modern physics, attracting many theoretical and experimental efforts towards its simulation. In this paper we propose that a simple model, in which fermions coupled to a dynamical lattice gauge field, can be engineered via the Floquet approach. The model possesses both an independent Maxwell term and local Z
2 gauge symmetry. Our proposal relies on a species-dependent optical lattice, and can be achieved in one, two or three dimensions. By a unitary transformation, this model can be mapped into a non-interacting composite fermion system with fluctuating background charge. With the help of this composite fermion picture, two characteristic observations are predicted. One is radio-frequency spectroscopy, which exhibits no dispersion in all parameter regimes. The second is dynamical localization, which depends on the structure of the initial states.
Microwave field sensor based on cold cesium Rydberg three-photon electromagnetically induced spectroscopy
Authors: Wu 吴 Yuan-Yuan 圆圆 , He 何 Yun-Hui 云辉 , Jiao 焦 Yue-Chun 月春 , Zhao 赵 Jian-Ming 建明 
Published: August 2024

Abstract
We present the electromagnetically induced transparency (EIT) spectra of cold Rydberg four-level cascade atoms consisting of the 6S1/2 → 6P3/2 → 7S1/2 → 60P3/2 scheme. A coupling laser drives the Rydberg transition, a dressing laser couples two intermediate levels and a weak probe laser probes the EIT signal. We numerically solve the Bloch equations and investigate the dependence of the probe transmission rate signal on the coupling and dressing lasers. We find that the probe transmission rate can display an EIT or electromagnetically induced absorption (EIA) profile, depending on the Rabi frequencies of the coupling and dressing lasers. When we increase the Rabi frequency of the coupling laser and keep the Rabi frequency of the probe and dressing laser fixed, flipping of the EIA to EIT spectrum occurs at the critical coupling Rabi frequency. When we apply a microwave field coupling the transition 60P3/2 → 61S1/2, the EIT spectrum shows Autler–Townes splitting, which is employed to measure the microwave field. The theoretical measurement sensitivity can be 1.52 × 10−2 nV⋅cm−1⋅Hz−1/2 at the EIA–EIT flipping point.
Research on 3D Reconstruction Algorithm of small Crops based on multi-view Geometry
Authors: Wang Haiman , Xiao Mingming , Luo Qintao , Luo Yuping 
Published: August 2024

Abstract
This paper presents a rapid 3D reconstruction method for phenotype analysis of small crops. Be aimed at the current difficult of high complexity and high equipment cost in acquiring point clouds based on laser scanning equipment, the authors directly use the images acquired by the common shooting equipment to complete the 3D reconstruction for citrus seedlings. A three-dimensional reconstruction architecture is established, it integrated the structure of motion recovery (SFM) algorithm, multi-view dense matching (CMVS+PMVS) based on cluster and facet models, and filtering of the generated three-dimensional model. The final result of this method is better, simpler, faster and more resistant to references.
A class of Schwarz qubit maps with diagonal unitary and orthogonal symmetries
Authors: Chruściński Dariusz , Bhattacharya Bihalan 
Published: August 2024

Abstract
A class of unital qubit maps displaying diagonal unitary and orthogonal symmetries is analyzed. Such maps have already found a lot applications in quantum information theory. We provide a complete characterization of this class of maps showing intricate relation between positivity, operator Schwarz inequality, and complete positivity. Finally, it is shown how to generalize the entire picture beyond unital case (so called generalized Schwarz maps). Interestingly, the first example of Schwarz but not completely positive map found by Choi belongs to our class. As a case study we provide a full characterization of Pauli maps. Our analysis leads to generalization of seminal Fujiwara–Algoet conditions for Pauli quantum channels.
Network topology and double delays in turing instability and pattern formation
Authors: Zheng Q Q , Li X , Shen J W , Pandey V , Guan L N 
Published: August 2024

Abstract
Investigating Turing patterns in complex networks presents a significant challenge, particularly in understanding the transition from simple to complex systems. We examine the network-organized SIR model, incorporating the Matthew effect and double delays, to demonstrate how network structures directly impact critical delay values, providing insights into historical patterns of disease spread. The study reveals that both susceptible and infected individuals experience a latent period due to interactions between the Matthew effect and incubation, mirroring historical patterns observed in seasonal flu outbreaks. The emergence of chaotic states is observed when two delays intersect critical curves, highlighting the complex dynamics that can arise in historical epidemic models. A novel approach is introduced, utilizing eigenvalue ratios from minimum/maximum Laplacian matrices (excluding 0) and critical delay values, to identify stable regions within network-organized systems, providing a new tool for historical epidemiological analysis. The paper further explores dynamic and biological mechanisms, discussing how these findings can inform historical and contemporary strategies for managing infectious disease outbreaks.
Wavelengths Selection Method in Near Infrared Spectra Using Multivariate Analysis for Nondestructive Determination of Oil Content in Palm Oil Fruits
Authors: Suci Y T , Budiastra I W , Purwanto Y A , Widodo S , Novianty I 
Published: August 2024

Abstract
Fruit oil content (FOC) is one of the most significant commercial characteristics in oil palm output both in upstream and downstream phases. The NIR Spectroscopy approach was used as a method to determine the oil content of fresh oil palm fruits. Several tests on the NIR spectroscopy approach for estimating the oil content of oil palm fruits revealed that the accuracy was still ideal when utilizing earlier spectra processing. Still, some crucial information was lost when using this spectra processing. Five hundred samples, categorized into ten groups according to their maturity levels, were readied for reflectance measurements and chemical assessments of oil content. The NIRFlex N-500 FT-NIR Spectrometer was employed to measure the reflectance of the samples within the 1000-1500 nm wavelength range. The acquired spectrum of fresh oil palm fruits was then converted to absorbance (Log 1/R). The method applied in this research is to select NIR absorption wavelengths that correlate with palm fruit oil content using PCA analysis and then develop a model using MLR. Five influential wavelengths were identified for predicting oil content of oil palm fruit based on the highest PC values in the loading plot of PCA those are 1166.59 nm, 1188.2 nm, 1212.4 nm, 1387 nm, and 1486 nm. The wavelength of 1212 nm (Ar) was selected as the reference of absorbance for establishment of MLR model, as A1, A2 and A3 were absorbances at the wavelengths of 1251.88, 1252.51 and 1468.86 nm, respectively. The established MLR model of Y= -14088.57 (A1/Ar) + 14017.9 (A2/Ar) – 12.24 (A3/Ar) + 120.67 can predict oil content of oil palm fruit (Y) accurately (R2 of 0.8 and SEP of 3.28 %). These findings show that the regression model has a strong capacity for prediction of oil content of palm fruits easily and nondestructively without the need for spectral preprocessing, solvents, or reagents, making it environmentally friendly.
The Effectiveness of Using Biofilter With the Addition of Palm Fibers on the Growth of Red Lettuce (Lactuca sativa var. Crispa) and Tilapia (Oreochromis niloticus) in Deep Flow Technique (DFT) Aquaponics Systems
Authors: Taufikurahman  , Wibawa M S M , Astutiningsih N T 
Published: August 2024

AbstractThe aquaponics system is a closed circulation system that uses interactions between plant and fish cultivation. Problems that often occur in the development of aquaponic systems, include the increase in the accumulation of toxins resulting from fish metabolites such as ammonia. The use of biofilters in the aquaponics system is expected to increase the transformation of ammonia into nitrates which can be used directly by plants. The addition of palm fiber to the bio-ball biofilter is expected to filter large particles in water. This research was conducted to determine the effect of adding palm fiber to the bio-ball biofilter on the growth of red lettuce (Lactuca sativa var. Crispa) and tilapia (Oreochromis chromis) growth. In addition, we also want to know whether there is an effect on plant growth based on different positions in the Deep Flow Technique (DFT) system model. This research was conducted in a Randomized Block Design (RBD) with 2 installations that had different biofilters and 5 plant positions in each installation. The first installation uses a bio-ball biofilter as a control and the second installation uses a bio-ball biofilter with the addition of palm fiber (1:1). In each installation, the effect of each plant position which has a different distance from the inlet was observed with the order of position 1 (30 cm); position 2 (60 cm); position 3 (90 cm); position 4 (120 cm); and position 5 (150 cm) on the growth of red lettuce (L. sativa). Each position treatment was repeated 12 times. Measurements were made on growth parameters and plant biomass, fish growth, water quality (pH, TDS, and EC), and environmental conditions (temperature, humidity, and light intensity). The data obtained were processed using a two-way ANOVA test and the BNJ Tukey test with a 95% confidence interval. The highest plant growth and plant biomass were obtained in the control biofilter treatment with positions 1 and 2. The highest fish growth was obtained in the palm fiber and bio-ball biofilter treatment. This is possibly caused by a decrease in nutrient levels due to the addition of palm fiber to the bioball biofilter. The addition of palm fiber can filter fish waste and large food scraps which also contain nutrients for plant growth so nutrients for red lettuce plant growth (L. sativa) are not optimal. Conversely, the addition of palm fiber to the bioball biofilter can improve water quality to support tilapia growth (O. niloticus).
Open source tools for OpenFOAM - Adaptive mesh refinement and convergence detection
Authors: Remmerie Wouter , Majksner Nikola 
Published: August 2024

Abstract
This paper presents two open-source tools to increase precision and automate CFD simulations in OpenFOAM. The first is an adaptive mesh refinement method which uses custom field properties to refine both volume and surface cells. The second is a method to detect convergence and dynamically size the length of the averaging window to obtain reliable averaged values.
Radiomics analysis of cerebral blood flow suggests a possible link between perfusion homogeneity and poor glioblastoma multiforme prognosis
Authors: Ebrahimi Behzad 
Published: August 2024

Abstract

Objectives. This study investigates the association between cerebral blood flow (CBF) and overall survival (OS) in glioblastoma multiforme (GBM) patients receiving chemoradiation. Identifying CBF biomarkers could help predict patient response to this treatment, facilitating the development of personalized therapeutic strategies. Materials and Methods. This retrospective study analyzed CBF data from dynamic susceptibility contrast (DSC) MRI in 30 newly diagnosed GBM patients (WHO grade IV). Radiomics features were extracted from CBF maps, tested for robustness, and correlated with OS. Kaplan-Meier analysis was used to assess the predictive value of radiomic features significantly associated with OS, aiming to stratify patients into groups with distinct post-treatment survival outcomes. Results. While mean relative CBF and CBV failed to serve as independent prognostic markers for OS, the prognostic potential of radiomic features extracted from CBF maps was explored. Ten out of forty-three radiomic features with highest intraclass correlation coefficients (ICC > 0.9), were selected for characterization. While Correlation and Zone Size Variance (ZSV) features showed significant OS correlations, indicating prognostic potential, Kaplan-Meier analysis did not significantly stratify patients based on these features. Visual analysis of the graphs revealed a predominant association between the identified radiomic features and OS under two years. Focusing on this subgroup, Correlation, ZSV, and Gray-Level Nonuniformity (GLN) emerged as significant, suggesting that a lack of heterogeneity in perfusion patterns may be indicative of a poorer outcome. Kaplan-Meier analysis effectively stratified this cohort based on the features mentioned above. Receiver operating characteristic (ROC) analysis further validated their prognostic value, with ZSV demonstrating the highest sensitivity and specificity (0.75 and 0.85, respectively). Conclusion. Our findings underscored radiomics features sensitive to CBF heterogeneity as pivotal predictors for patient stratification. Our results suggest that these markers may have the potential to identify patients who are unlikely to benefit from standard chemoradiation therapy.