bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utility of Surgical Apgar Score in Predicting Post-operative Complications After Whipple Procedure in Pancreatic Cancer Patients
Authors: Howbora Nilanjana , Thota Raghu S. , Pargunde Sagar , Patil Vijaya , Agarwal Vandana , Bhandare Manish , Shrikhande Shailesh V. 
Published: December 2024

AbstractAn intraoperative 10-point Surgical Apgar Score, based on estimated blood loss, lowest mean arterial pressure, and lowest heart rate, was developed and validated for predicting postoperative complications in patients undergoing vascular and general surgeries. We sought to estimate the ability of this metric to predict major postoperative complications in patients with pancreatic cancer undergoing the Whipple procedure. This is a prospective, observational, single-centre study involving adult patients undergoing the Whipple procedure, at a major tertiary cancer centre. All eligible patients undergoing Whipple surgery in our institute between March 2018 and October 2021 were included in the study. Demographic data, clinicopathological characteristics, comorbidities, intraoperative variables, and postoperative complications were analyzed. The surgical score was calculated from intraoperative blood loss, lowest heart rate, and lowest mean arterial pressure. All the patients were followed up till 30 days postoperatively. Descriptive statistics and univariate and multivariate analyses were used as appropriate. The occurrence of major postoperative complications represented the primary outcome. A total of 253 patients were analyzed. The mean duration of surgery was 436 min. On statistical analyses, the occurrence of major postoperative complications was significantly associated with SAS ≤ 4 (OR = 8.00, 95% CI = 3.78–16.93, p = 0.000), use of intraoperative vasopressor (OR = 2.247, 95% CI = 1.312–3.846, p = 0.003), and body mass index (BMI) (OR = 1.074, 95% CI = 1.010–1.142, p = 0.022). However, we did not find any significant association between other demographic variables like age, comorbidities, duration of surgery, and preoperative s. albumin with the occurrence of postoperative complications. Lower SAS (≤ 4) is the most powerful predictor of postoperative complications in pancreatic cancer patients undergoing Whipple surgery. The score provides a simple and immediate means of measuring and communicating patient outcomes, using data routinely available in any setting.
Advances in tabulating Carmichael numbers
Authors: Shallue Andrew , Webster Jonathan 
Published: December 2024

AbstractWe report that there are 49679870 Carmichael numbers less than $$10^{22}$$

10
22

which is an order of magnitude improvement on Richard Pinch’s prior work. We find Carmichael numbers of the form $$n = Pqr$$

n
=
P
q
r

using an algorithm bifurcated by the size of P with respect to the tabulation bound B. For $$P < 7 \times 10^7$$

P
<
7
×

10
7

, we found 35985331 Carmichael numbers and 1202914 of them were less than $$10^{22}$$

10
22

. When $$P > 7 \times 10^7$$

P
>
7
×

10
7

, we found 48476956 Carmichael numbers less than $$10^{22}$$

10
22

. We provide a comprehensive overview of both cases of the algorithm. For the large case, we show and implement asymptotically faster ways to tabulate compared to the prior tabulation. We also provide an asymptotic estimate of the cost of this algorithm. It is interesting that Carmichael numbers are worst case inputs to this algorithm. So, providing a more robust asymptotic analysis of the cost of the algorithm would likely require resolution of long-standing open questions regarding the asymptotic density of Carmichael numbers.
Application of a Scale Normalization Technique for High Resolution Analysis of the Magnetosheath at Mars
Authors: Fruchtman Jacob , Halekas Jasper , Eparvier Francis G. , Gruesbeck Jacob , Mazelle Christian , Mitchell David 
Published: December 2024

AbstractIn order to study spatial distributions of global magnetosheath structures, physicists often rely upon spatial binning, whereby space is divided into cells, each filled with the average value of all spacecraft measurements within that cell. The traditional binning schema utilizes a fixed Cartesian grid of cube bins. The morphology of the magnetosheath's boundaries are not fixed, however, but driven by upstream and planetary conditions. Therefore, the spatial structures are not fixed in Cartesian space, and thus a Cartesian binning technique will produce a highly coarse grained spatial distribution. We propose an alternative binning technique utilizing a scale normalized dimensionless coordinate system defined in terms of magnetosheath morphology. To demonstrate the efficacy of this technique, we apply a basic implementation to the Martian system. We are thereby able to achieve a high‐resolution spatial mapping of bow shock and magnetosheath processes and resolve spatial structures that are washed out when binned traditionally. In particular, we can resolve the shock overshoot, analyze the dominant forces acting at the shock, and obtain fine‐scale distributions of the bulk ion plasma magnetosheath forces and thermalization mechanisms. Magnetic tension and magnetic pressure gradient are compared. The ion pressure divergence at the shock is found to significantly vary in line with the solar wind temperature anisotropy. The dependency of the mirror mode instability on location and Mach number, and its implications for thermalization processes in the small Martian magnetosheath are investigated.
Exploring Optimal Complexity for Water Stress Representation in Terrestrial Carbon Models: A Hybrid‐Machine Learning Model Approach
Authors: Fang J. , Gentine P. 
Published: December 2024

AbstractTerrestrial biosphere models offer a comprehensive view of the global carbon cycle by integrating ecological processes across scales, yet they introduce significant uncertainties in climate and biogeochemical projections due to diverse process representations and parameter variations. For instance, different soil water limitation functions lead to wide productivity ranges across models. To address this, we propose the Differentiable Land Model (DifferLand), a novel hybrid machine learning approach replacing unknown water limitation functions in models with neural networks (NNs) to learn from data. Using automatic differentiation, we calibrated the embedded NN and the physical model parameters against daily observations of evapotranspiration, gross primary productivity, ecosystem respiration, and leaf area index across 16 FLUXNET sites. We evaluated six model configurations where NNs simulate increasingly complex soil water and photosynthesis interactions against test data sets to find the optimal structure‐performance tradeoff. Our findings show that a simple hybrid model with a univariate NN effectively captures site‐level water and carbon fluxes on a monthly timescale. Across a global aridity gradient, the magnitude of water stress limitation varies, but its functional form consistently converges to a piecewise linear relationship with saturation at high water levels. While models incorporating more interactions between soil water and meteorological drivers better fit observations at finer time scales, they risk overfitting and equifinality issues. Our study demonstrates that hybrid models have great potential in learning unknown parameterizations and testing ecological hypotheses. Nevertheless, careful structure‐performance tradeoffs are warranted in light of observational constraints to translate the retrieved relationships into robust process understanding.
Strong Relativistic Electron Flux Events in GPS Orbit
Authors: Meredith Nigel P. , Cayton Thomas E. , Cayton Michael D. , Horne Richard B. 
Published: December 2024

AbstractRelativistic electrons cause internal charging on satellites and are a significant space weather hazard. In this study we analyze approximately 20 years of data from the US Global Positioning System (GPS) satellite NS41 to determine the conditions associated with the largest daily averaged fluxes of = 2.0 MeV relativistic electrons. The largest flux events at = 4.5 and = 6.5 were associated with moderate to strong CME‐driven geomagnetic storms. However, the majority of the 50 largest flux events at = 4.5 (30 out of 50) and = 6.5 (37 out of 50) were associated with high speed solar wind streams from coronal holes. Both solar drivers are thus very important for relativistic electron flux enhancements in GPS orbit. The 1 in 3 year flux level was not exceeded following any of the 15 largest geomagnetic storms as monitored by the index, showing that the largest geomagnetic storms, most often associated with extreme space weather, do not result in significantly larger relativistic electron flux events in GPS orbit.
Computationally efficient data‐driven model predictive control for modular multilevel converters
Authors: Raja Muneeb Masood , Wang Haoran , Arshad Muhammad Haseeb , Kish Gregory J. , Zhao Qing 
Published: December 2024

AbstractThe application of model predictive control (MPC) for the control of modular multilevel converters (MMCs) is widely explored because it offers flexibility in integrating multiobjective control and delivers superior dynamic response. Nonetheless, the increase in computational complexity due to the rise in the number of submodules (SMs) is one of the major drawbacks of this technique. This paper presents a finite control set model predictive control (FCS‐MPC) that significantly reduces the computational complexity by employing sparse identification of non‐linear systems (SINDy) to obtain a simplified linear model for the MMC. The SINDy model reduces the complexity of performing the prediction step by integrating input terms into the dynamics of load current and circulating current. This simplifies the implementation compared to the conventional FCS‐MPC approaches by eliminating the need to evaluate the voltage dynamics. The computational burden is further reduced while maintaining voltage levels at the output by restricting the number of combinations for the inserted SMs to only instead of . A detailed comparison between the proposed technique and the existing strategies demonstrates that the proposed technique offers a more computationally efficient solution for implementing FCS‐MPC on MMCs, while improving the circulating current suppression due to more accurate predictions. Simulation and experimental results are presented to validate the performance of the proposed approach.
Improving coverage of indoor millimetre wave systems using spherical reflectors
Authors: Qualtrough‐Mittal Priya A. , Neve Michael J. , Austin Andrew C. M. 
Published: December 2024

AbstractThe increased demand for user device connectivity has led to spectral congestion which is driving exploration of higher frequency spectrum, such as millimetre wave frequencies. As millimetre wave propagation is predominantly line‐of‐sight, shadowing becomes prevalent in indoor environments due to obstructions from clutter. Accordingly, there is a need to find solutions which can provide additional coverage. In this work, octant‐shaped spherical reflectors are deployed in small office environments with varying degrees of clutter to provide additional ray paths to improve millimetre wave coverage into shadow regions. Cost weightings have been allocated to prioritise regions of high importance and are used to compare reflector deployment strategies. Appropriate positioning of reflectors in the environment is shown to improve coverage into shadow regions in all three environments considered, with placement in the top corners of a room found to be a valid solution. In densely cluttered environments, more than one reflector may be required to provide sufficient coverage. Reducing the reflector radius by 0.1 m has been shown to increase reflected power by up to 6 dB in some cases.
Advanced beamforming and reflection control in intelligent reflecting surfaces with integrated channel estimation
Authors: Monga Sakhshra , Singh Anmol Rattan , Saluja Nitin , Prabha Chander , Malhotra Shivani , Karim Asif , Hassan Md. Mehedi 
Published: December 2024

AbstractIntelligent Reflecting Surfaces (IRS) enhance wireless communication by optimising signal reflection from the base station (BS) towards users. The passive nature of IRS components makes tuning phase shifters difficult and direct channel measurement problematic. This study presents a machine learning framework that directly maximises the beamformers at the BS and the reflective coefficients at the IRS, bypassing conventional methods that estimate channels before optimising system parameters. This is achieved by mapping incoming pilot signals and data, including user positions, with a deep neural network (DNN), guiding an optimal setup. User interactions are captured using a permutation‐invariant graph neural network (GNN) architecture. Simulation results show that implicit channel estimation method requires fewer pilots than standard approaches, effectively learns to optimise sum rate or minimum‐rate targets, and generalises well. Specifically, the sum rate for GDNNet (GNN + DNN) improves by over linear minimum mean square error (LMMSE) and by over perfect CSI concerning the number of users, and by over LMMSE and by over perfect CSI concerning pilot length. Offering a feasible solution with reduced computing complexity for real‐world applications, the proposed GNN + DNN method outperforms conventional model‐based techniques such as LMMSE and approaches the performance of perfect CSI, demonstrating its high effectiveness in various scenarios.
Thermal analysis of mineral oil‐based nanofluids of distribution transformers exposed to simultaneous current and voltage harmonics
Authors: Abdali Ali , Mazlumi Kazem , Rabiee Abbas 
Published: December 2024

AbstractThe exact thermal evaluation of distribution transformers (DTs), which are critical and costly pieces of equipment for the power grids, may contribute to preventing the respective failures. Therefore, the present study non‐uniformly investigated DT for correct anticipation of hotspot temperature (HST). Optical fibre sensors (OFSs) were applied for assessing our newly developed non‐uniform 3D computational fluid dynamic (CFD)‐based modelling while performing the temperature rise test (TRT). It should be noted that this new 3D CFD‐based thermal analysis showed an error percentage of 0.11% (0.1°C) in comparison to the OFS measurement, reflecting the ideal efficiency and accuracy of the model. Moreover, thermography for both top‐oil temperature (TOT) and bottom‐oil temperature (BOT) was employed to validate the results from non‐uniform 3D (three‐dimensional) CFD‐based thermal evaluations. The results indicated an acceptable level of relationship between thermography and thermal analysis of 3D CFD at the specified two spots, with an error percentage of <0.65%, demonstrating the acceptable accuracy of the new non‐uniform 3D CFD‐based model. In the following, yet importantly, the new non‐uniform 3D model was subjected to the total harmonic distortions (THD) for the current and voltage of 5%, 10%, and 15%, which raised the HST more than the original model without harmonics by 3.3°C, 7.1°C, and 10.3°C, respectively. Ultimately, different mineral oil‐based nanofluids’, such as multi‐walled carbon nanotubes (MWCNTs) and diamond nanoparticles, influence on the HST decrement of DT in simultaneous current and voltage harmonics was investigated.
Low‐frequency oscillation damping strategy for power system based on virtual dual‐input power system stabilizer
Authors: Lu Shengyang , Wu Meng , Liu Jia , Wang Haixin , Yang Luyu , Liu Qingshan , Yang Junyou , Sui Yuqiu 
Published: December 2024

AbstractTo keep pace with the construction of the new‐type power system, virtual synchronous generator control, as a classical method of virtual inertia control, has been widely adopted due to its electromechanical characteristics similar to synchronous generator. However, the introduction of rotor motion equations leads to low‐frequency oscillation issues in virtual synchronous generator units similar to synchronous machines. To address this challenge, this paper constructs the Phillips‐Heffron model of the virtual synchronous generator grid‐connected system and analyses the mechanism of low‐frequency oscillation in virtual synchronous generator through the damping torque method. Subsequently, a virtual dual‐input power system stabilizer is proposed by drawing inspiration from the design principles of the traditional dual‐input power system stabilizer to suppress low‐frequency oscillations in the power system. The structure of the virtual dual‐input power system stabilizer is provided, and the phase compensation method is used to optimize the parameters of the virtual dual‐input power system stabilizer. Finally, the effectiveness of the proposed virtual dual‐input power system stabilizer is verified by simulation comparison.
Use of a Novel Virtual Reality-Based Pupillography Device for Glaucoma Management: Cross-Sectional Cohort Pilot Study
Authors: El-Koussy Karim , Höhn René , Falcão Mariana B. L. , Hauser Bruno , Naidu Avantika , Abegg Mathias 
Published: December 2024

Abstract
Background Current standard methods in monitoring glaucoma progression, like optical coherence tomography (OCT) and standard automated perimetry (SAP), have limitations in certain cases. Automated relative afferent pupillary defect (RAPD) and pupillary light reflex (PLR) testing may offer more objective alternatives. This pilot study aimed to evaluate whether RAPD could sufficiently distinguish between the two eyes in asymmetrical glaucoma, and thus could lay the foundation for using the PLR of a single eye to monitor progression longitudinally.
Methods Twenty-one patients underwent quantitative PLR measurements using a virtual reality headset. RAPD was calculated by subtracting the amplitude of PLRs between eyes. Both RAPD and relative SAP (measured using the mean defect or MD) results were correlated to the thickness of the peripapillary retinal nerve fiber layer (RNFL), as measured by OCT.
Results Data from 18 patients was analyzed after exclusions. RAPD significantly correlated with differences between the two eyes as measured by RNFL thickness (Pearson r = 0.79, p = 0.05). MD differences correlated slightly better with RNFL differences (Pearson r = 0.87, p < 0.05). RAPD and MD combined yielded an improved prediction of RNFL differences by 5% compared to using MD only.
Conclusions RAPD measurements reliably detected asymmetries in optic nerve damage in glaucoma patients. SAP measurements correlated better with OCT results than RAPD results. However, SAP and RAPD combined led to an improved prediction of RNFL thickness. This could possibly allow us to use PLR only over longer periods of time to monitor glaucomatous optic nerve damage in a single eye in the future.
Alignment Strategies in Total Knee Arthroplasty: The Rise and Role of Enabling Technology
Authors: Chen Darren B. 
Published: December 2024

AbstractTotal knee arthroplasty (TKA) remains the gold standard surgical care for end-stage knee arthritis. Since its inception, TKA has seen many transformative factors with advances in material properties, implant design, and fixation. Improvements in implant longevity has culminated in TKA being recognized as one of modern medicine's most successful surgical procedures. Patient satisfaction, however, remains a significant challenge. Recent studies report that patient satisfaction with current implants and techniques remains at 80 to 90%, suggesting that up to one in five patients remain dissatisfied with their procedure. A balanced knee, defined as equal medial and lateral gaps in knee extension and flexion, is a desired outcome in TKA. This has been shown to be associated with improved clinical outcomes. Given the poor rate of surgeon-defined balance, intraoperative knee balance can be confirmed with objective load data using sensor-embedded smart inserts or by measuring gaps using computer-assisted or robotic platforms. Currently, there is no consensus on the correct alignment or laxity targets for individualized alignment strategies in TKA, and further research in this area is required to answer this. Tremendous advances in our understanding of knee anatomy and kinematics have come to light in the recent past, and these insights have spawned interest in alternative alignment techniques in TKA. More recently, an appreciation of individual knee phenotypes and associated classification systems have provided a platform and the scientific justification behind these contemporary alignment strategies. Paired with enabling technologies, it is becoming an accepted paradigm that surgeons have the ability to select a desired alignment target when undertaking an individualized alignment strategy in TKA and execute the surgery with a high degree of precision. It is hoped that this may reduce the rate of dissatisfaction following TKA and improve clinical outcomes. This review article provides an overview of the concepts of knee phenotypes, current alignment strategies in TKA, and the emerging benefits of enabling technologies.
Recent Advances in the Synthesis of Sulfonamides Intermediates
Authors: Liu Wei , Chen Jianli , Su Weike 
Published: December 2024

AbstractSulfonamides are one of the most important synthons in drug synthesis, which can increase the water solubility of drugs and regulate their metabolism in vivo. According to statistics, nearly 30% of sulfur-containing drugs on the market contain sulfonamide groups, including omeprazole, hydrochlorothiazide, and other best-selling drugs. Synthesis of sulfonamide is therefore a very important part of new drug development and active pharmaceutical ingredient manufacturing. In this review, we will focus on the recent 5-year advances in the field of synthetic research and structural modification of sulfonamide-containing drugs and their intermediates. The synthesis strategies, including S−N construction, C−N cross-coupling, N−H functionalization, and C−H sulfonamidation, are discussed, hoping to provide new ideas for the researchers to prepare sulfonamides in a green and efficient way.
The what and when of word retrieval in spoken language
production
Authors: Mahon Bradford Z. , Navarrete Eduardo 
Published: December 2024

Abstract
Semantically driven lexical access in spoken
language production is the process of transposing a communicative
intention into phono-articulatory codes. At each stage of
processing, from lexical-semantic retrieval through to
phono-articulatory processing, more representations are active than
are minimally necessary to produce the target word. In recognition
of that fact, research over the past three decades has been driven
by a (putative) need to answer a core question: How is conflict
resolved at the lexical level? The ‘standard view’ involves some
form of the idea that selection of the target word is governed by a
stochastic process implemented via a biased competition mechanism,
with the nature of the ‘bias’ differing quite widely across
proposals. Here we argue that the standard view is out of synchrony
with a range of findings; interestingly, and as a matter of historical
precedent, a number of those findings pre-date the earliest
formulations of the standard view. Stepping back, we argue for a new
approach to framing the question of word retrieval: no mechanism is
needed to resolve conflict at the lexical level, because there is no
conflict at the lexical level. Selection occurs at
the semantic/message level. After selection of the intended meaning
representation, the next opportunity in the processing pathway to
re-evaluate which word to produce is at the level
of the pre-articulatory response monitor. We refer to this as a
‘ballistic’ model of word retrieval to emphasize there is no
uncertainty about the identity of the target
word at the lexical level, and that retrieval of
the correct representation at that level can be sped up, but not
slowed down.