bluuebunny/crossref_metadata_2025_split huggingface dataset:
Infección asociada a fractura ¿Qué nos dice la literatura?
Authors: Pineda Tomás , Fuentealba Andrés , Zamorano Álvaro 
Published: May 2024

ResumenLa infección asociada a fracturas (IAF) es una de las complicaciones más frecuentes y desafiantes del trauma ortopédico, sin embargo, su importancia ha sido subestimada existiendo históricamente una falta de estandarización en su manejo. En los últimos años la evidencia científica disponible ha ido en aumento, y a consecuencia de ello múltiples guías clínicas y consensos de expertos han sido publicados.El objetivo de este trabajo es proporcionar una actualización, dirigida principalmente a especialistas en Ortopedia y Traumatología, buscado estandarizar criterios diagnósticos y de tratamiento basado en evidencia científica reciente.
A Narrative Review of Neurological Complications of SARS-CoV-2 Vaccination
Authors: Bithal Parmod K. , Rajagopalan Vanitha 
Published: May 2024

AbstractAdverse reactions to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine depict a tropism for neural structures. This narrative review was aimed to discuss published data on the spectrum of neurological side effects of SARS-CoV-2 vaccines, which were accorded emergency use authorization. The majority of the neurological manifestations of SARS-CoV-2 vaccination are usually mild, brief, self-limiting, and easily manageable. Rarely, these side effects can be of serious nature and require hospitalization. High vigilance helps in early identification and treatment of these complications leading to good outcomes. The reported incidence of neurological complications in vaccinated population is a miniscule, and the overall benefits of the vaccine outweigh the risks of side effects. However, it is crucial to conduct larger collaborative multicenter studies to prove or reject the causal association between the SARS-CoV-2 vaccines and the postvaccination neurological side effects. Herein, we have tried to summarize the various neurological manifestations related to SARS-CoV-2 vaccines published in the literature from 2021 to mid-2023.
Tracking Wall Characteristics of Necrotic Pancreatic Fluid Collections in Acute Pancreatitis on Serial Contrast-Enhanced Computed Tomography
Authors: Bhatia Harsimran , Johnson Joseph , T. Pallavi , Gupta Pankaj , Gulati Ajay , Shah Jimil , Singh Anupam , Jearth Vaneet , Samanta Jayanta , Mandavdhare Harshal , Sharma Vishal , Sinha Saroj K. , Dutta Usha , Kocchar Rakesh 
Published: May 2024

Abstract
Background Encapsulated pancreatic fluid collection (PFC) is a requisite for endoscopic drainage procedures. The 4-week threshold for defining walled-off necrosis does not capture the dynamic process of encapsulation. We aim to investigate the changes in the wall characteristics of PFC in acute necrotizing pancreatitis (ANP) by comparing baseline contrast-enhanced computed tomography (CECT) with follow-up CT scans.
Methods This retrospective study comprised consecutive patients with ANP who underwent a baseline CECT within first 2 weeks and follow-up CECT in the third to fifth weeks of illness. Presence, extent, and encapsulation thickness (defined as enhancing wall around the collection) on baseline CECT were compared with follow-up CT (done in the third–fifth weeks of illness).
Results Thirty patients (19 males and 11 females; mean age 41.5 ± 13.5 years) were included in the study. The mean time to first CECT was 10 ± 3.6 days. There were 58 collections. The most common site was the lesser sac (n = 29), followed by the left pararenal space (n = 15). At baseline CT, 52 (89.7%) collections had varying degree of encapsulation (15.3%, complete encapsulation). Complete encapsulation was seen in 52 and 82.6% collections in third and fourth week, respectively. All collections in fifth week and beyond were encapsulated. The wall was thicker on follow-up CECT scans (p < 0.01). The mean wall thickness was not significantly associated with the degree of encapsulation (p = 0.417). There was no significant association between the site and degree of encapsulation (p = 0.546).
Conclusion Encapsulation is dynamic and collections may get “walled off” before 4 weeks. Walled-off collections should be defined based on imaging rather than a fixed 4-week revised Atlanta classification threshold.
Tratamiento de la contractura en flexión de rodilla en parálisis cerebral
Authors: Martinez Gino , Segovia Javier , Cariola Martín 
Published: May 2024

ResumenLa extensión completa de la rodilla es esencial para la marcha. Los pacientes con parálisis cerebral infantil con frecuencia pueden tener déficit de extensión de distinta magnitud, lo que compromete la marcha e incluso la bipedestación. El tratamiento de la contractura en flexión de rodilla parte por tratar la espasticidad de los músculos comprometidos y con fisioterapia. Cuando el flexo es estructurado, el tratamiento es quirúrgico mediante distintas técnicas, dependiendo de la magnitud de la contractura y de la edad del paciente. Las técnicas sobre partes blandas incluyen alargamientos funcionales de isquiotibiales y transferencias musculares. Cuando la contractura es capsular, es preferible realizar cirugía ósea, la cual extiende el fémur proximal, ya sea en forma progresiva, mediante fisiodesis anterior en pacientes pediátricos, o en forma aguda, mediante osteotomía extensora del fémur distal. Con frecuencia existe una patela alta, la cual hay que corregir en el mismo acto quirúrgico para mantener la eficiencia del aparato extensor.
Magnetic hysteresis mechanism in Lu0.9Sr0.1Cr0.5Fe0.5O3 studied by Monte Carlo simulations
Authors: Lurgo Florencia E , Sánchez Rodolfo D , Carbonio Raúl E , Billoni Orlando V 
Published: May 2024

Abstract
In this work we report magnetic properties of the orthorhombic perovskite Lu0.9Sr0.1Cr0.5Fe0.5O3 synthesized by a wet chemical method. As in LuCr0.5Fe0.5O3 the compound with Sr shows the magnetization reversal phenomenon, but the magnetic order and the compensation temperature occur at higher temperatures. Interestingly, in M vs H curves a hysteresis loop is observed when Cr4+ and Cr3+ ions coexist as a consequence of the aliovalent substitution of Lu3+ by Sr2+ in the B sites of the perovskite. To explain this behavior, we performed numerical simulations with a magnetic model for Lu1−x
Sr
x
Cr0.5Fe0.5O3 perovskites with x= 0 and x = 0.1. We found that the ferromagnetic coupling of Fe3+ and Cr4+ through superexchange interactions (according the empiric Goodenough–Kanamori–Anderson rules) increases the magnetization at high fields and that the presence of ferromagnetic clusters explains the hysteretic behavior found in simulations.
Coupled quintessence scalar field model in light of observational datasets
Authors: Patil Trupti , Ruchika  , Panda Sukanta 
Published: May 2024

Abstract
We do a detailed analysis of a well-theoretically motivated interacting dark energy scalar field model with a time-varying interaction term. Using current cosmological datasets from CMB, BAO, Type Ia Supernova, H(z) measurements from cosmic chronometers, angular diameter measurements from Megamasers, growth measurements, and local SH0ES measurements, we found that dark energy component may act differently than a cosmological constant at early times. The observational data also does not disfavor a small interaction between dark energy and dark matter at late times.
When using all these datasets in combination, our value of H
0 agrees well with SH0ES results but in 2.5σ tension with Planck results. We also did AIC and BIC analysis, and we found that the cosmological data prefer coupled quintessence model over ΛCDM, although the chi-square per number of degrees of freedom test prefers the latter.
Probabilistic stimulation mapping from intra-operative thalamic deep brain stimulation data in essential tremor
Authors: Vogel Dorian , Nordin Teresa , Feiler Stefanie , Wårdell Karin , Coste Jérôme , Lemaire Jean-Jacques , Hemm Simone 
Published: May 2024

Abstract
Deep brain stimulation (DBS) is a therapy for Parkinson’s disease (PD) and essential tremor (ET). The mechanism of action of DBS is still incompletely understood. Retrospective group analysis of intra-operative data recorded from ET patients implanted in the ventral intermediate nucleus of the thalamus (Vim) is rare. Intra-operative stimulation tests generate rich data and their use in group analysis has not yet been explored. Objective. To implement, evaluate, and apply a group analysis workflow to generate probabilistic stimulation maps (PSMs) using intra-operative stimulation data from ET patients implanted in Vim. Approach. A group-specific anatomical template was constructed based on the magnetic resonance imaging scans of 6 ET patients and 13 PD patients. Intra-operative test data (total: n = 1821) from the 6 ET patients was analyzed: patient-specific electric field simulations together with tremor assessments obtained by a wrist-based acceleration sensor were transferred to this template. Occurrence and weighted mean maps were generated. Voxels associated with symptomatic response were identified through a linear mixed model approach to form a PSM. Improvements predicted by the PSM were compared to those clinically assessed. Finally, the PSM clusters were compared to those obtained in a multicenter study using data from chronic stimulation effects in ET. Main results. Regions responsible for improvement identified on the PSM were in the posterior sub-thalamic area (PSA) and at the border between the Vim and ventro-oral nucleus of the thalamus (VO). The comparison with literature revealed a center-to-center distance of less than 5 mm and an overlap score (Dice) of 0.4 between the significant clusters. Our workflow and intra-operative test data from 6 ET-Vim patients identified effective stimulation areas in PSA and around Vim and VO, affirming existing medical literature. Significance. This study supports the potential of probabilistic analysis of intra-operative stimulation test data to reveal DBS’s action mechanisms and to assist surgical planning.
FetchEEG: a hybrid approach combining feature extraction and temporal-channel joint attention for EEG-based emotion classification
Authors: Liang Yu , Zhang Chenlong , An Shan , Wang Zaitian , Shi Kaize , Peng Tianhao , Ma Yuqing , Xie Xiaoyang , He Jian , Zheng Kun 
Published: May 2024

Abstract

Objective. Electroencephalogram (EEG) analysis has always been an important tool in neural engineering, and the recognition and classification of human emotions are one of the important tasks in neural engineering. EEG data, obtained from electrodes placed on the scalp, represent a valuable resource of information for brain activity analysis and emotion recognition. Feature extraction methods have shown promising results, but recent trends have shifted toward end-to-end methods based on deep learning. However, these approaches often overlook channel representations, and their complex structures pose certain challenges to model fitting. Approach. To address these challenges, this paper proposes a hybrid approach named FetchEEG that combines feature extraction and temporal-channel joint attention. Leveraging the advantages of both traditional feature extraction and deep learning, the FetchEEG adopts a multi-head self-attention mechanism to extract representations between different time moments and channels simultaneously. The joint representations are then concatenated and classified using fully-connected layers for emotion recognition. The performance of the FetchEEG is verified by comparison experiments on a self-developed dataset and two public datasets. Main results. In both subject-dependent and subject-independent experiments, the FetchEEG demonstrates better performance and stronger generalization ability than the state-of-the-art methods on all datasets. Moreover, the performance of the FetchEEG is analyzed for different sliding window sizes and overlap rates in the feature extraction module. The sensitivity of emotion recognition is investigated for three- and five-frequency-band scenarios. Significance. FetchEEG is a novel hybrid method based on EEG for emotion classification, which combines EEG feature extraction with Transformer neural networks. It has achieved state-of-the-art performance on both self-developed datasets and multiple public datasets, with significantly higher training efficiency compared to end-to-end methods, demonstrating its effectiveness and feasibility.
Development of a floating Vertical Axis Wind Turbine for the Mediterranean Sea
Authors: Ghigo Alberto , Petracca Ermando , Mangia Gabriele , Giorgi Giuseppe , Bracco Giovanni 
Published: May 2024

Abstract
Differently from Horizontal Axis Wind Turbines (HAWTs), which are the reference technologies in the wind market for their reliability and maturity, Vertical Axis Wind Turbine (VAWT) applications are related to small-scale contexts, such as providing electricity in isolated areas or urban settings. Consequently, the capacity of VAWTs results significantly lower than the order of megawatts and does not exceed a few tens of kilowatts. A promising field of application for VAWTs is the floating offshore: among the main advantages there are an increased static stability, by placing the rotor-nacelle assembly (RNA) at the base of the VAWT and reduced operational and maintenance (O&M) costs. Moreover, the different wake dynamics allows to reduce the aerodynamic losses, allowing closer turbine installations. However, to be competitive with floating HAWTs, it is necessary to have numerical models for the analysis and simulation of multi-megawatt VAWTs. This paper aims to introduce a time domain model of a floating vertical axis wind turbine, developed within the Matlab-Simscape environment. The model comprises an aerodynamics module, based on Double Multiple Stream Tube theory while hydrodynamics is modelled using WEC-Sim. A case study, involving a Darrieus H-rotor VAWT tested in the Mediterranean Sea and supported by a semi-sub foundation, the OC4-DeepCwind, is introduced. The results obtained are compared with those from QBlade, an software developed by TU Berlin, demonstrating a good agreement between the two codes.
A polyurethane solid-solid composite phase change material based on modified graphene oxide for efficient thermal management
Authors: Yang X , Liao Y N , Li J , Mao Y , Chen S S , Sun K , Li M , Zheng Y J 
Published: May 2024

Abstract
Solid-solid phase change materials (SSPCMs) are potential materials for energy storage and thermal management, and improving mechanical property and heat transfer performance is the key to practical application. After modified graphene oxide (TGO) was prepared by toluene diisocyanate, a kind of super-tough, form-stable and leak-proof polyurethane composite phase change material (PU-TGO) was constructed by the two-step polymerization of isophorone diisocyanate and 1, 4-butanediol using polyethylene glycol and TGO. TGO has more uniform and stable dispersion than traditional graphene oxide, and its chemical crosslinking with polyurethane phase change materials makes the composite have better shape stability, mechanical strength, thermal conductivity and flexibility. PU-TGO has thermal conductivity and elongation at break up to 0.3072 W/(m•K) and 540%, respectively, and maintains excellent thermal stability and 72.09 J/g enthalpy after 500 thermal cycles. PU-TGO prepared by chemical crosslinks in this paper further demonstrates the great potential of phase change materials in the field of thermal management of new electronic devices.
Fabrication and properties of SiC-based accident-tolerant fuel with precisely-regulated TRISO particles dispersion
Authors: Shao Zongyi , Zhao Yumeng , Feng Shuaishuai , Meng Ying , Chen Chen , Lui Wentao , Liu Wei , Cai Zhenfang 
Published: May 2024

Abstract
The ceramic-based coated particle dispersed fuel (CDF) has arrested worldwide attention as a kind of promising accident-tolerant fuel since the Fukushima-Daiichi accident in 2011. To improve safety and in-pile performance, regularly-distributed CDF was formulated. A novel fabrication method was developed to accurately target TRistructural-ISOtropic (TRISO) particles to preset positions in the SiC matrix via a self-developed precise TRISO-controlled moulding equipment. After sintering, the samples were observed by SEM and X-μCT, which showed that the TRISO particles were uniformly and regularly arranged in the SiC matrix, and were almost intact with little extrusion and breakage. The density, thermal conductivity, and thermal shock performance of the prepared samples were examined and proved to be consistent with those of the pellets with randomly-distributed TRISO particles, which could satisfy the safety requirements. Small batch manufacturing was realized and production efficiency was enhanced. This new technology offers a promising pathway to produce high-reliability ceramic-based CDF with precisely-located TRISO particles, which promote the development of advanced accident-tolerant fuels.
Drag reduction in a minimal channel flow with scientific multi-agent reinforcement learning
Authors: Wälchli D , Guastoni L , Vinuesa R , Koumoutsakos P 
Published: May 2024

Abstract
We study drag reduction in a minimal turbulent channel flow using scientific multi-agent reinforcement learning (SMARL). The flow is controlled by blowing and suction at the wall of an open channel, with observable states derived from flow velocities sensed at adjustable heights. We explore the actions, state, and reward space of SMARL using the off-policy algorithm V-RACER. We compare single- and multi-agent setups, and compare the identified control policies against the well-known mechanism of opposition-control. Our findings demonstrate that off-policy SMARL reduces drag in various experimental setups, surpassing classical opposition-control by up to 20 percentage points.
Switching between slow light and fast light by static magnetic field in a degenerate four-level atomic system at room temperature
Authors: Van Phu Nguyen , Bang Nguyen Huy , Nga Luong Thi Yen , Doai Le Van 
Published: May 2024

Abstract
The optical response of a magnetic-degenerated four-level atom system to the two left and right circular polarization components of the probe field is represented at room temperature. The absorption spectrum and group index for the two polarization components of the probe field are controlled according to the static magnetic field and the coupling field under electromagnetically induced transparency condition. By varying the strength of the static magnetic field, the optical response of the atomic medium can be changed from transparency to absorption or vice versa and hence the amplitude of group index also changes from positive extreme to negative extreme or vice versa. The same phenomenon also occurs when changing the coupling field intensity. In addition, temperature also significantly influence on the optical response of the atomic medium, which changes not only the amplitude but also the sign of the group index as the temperature increases. Our analytical results can be useful for experimental observation and related applications of light group index/velocity at room temperature.
Role of chalcogen vacancies and hydrogen in the optical and electrical properties of bulk transition-metal dichalcogenides
Authors: Khalid Shoaib , Janotti Anderson , Medasani Bharat 
Published: May 2024

Abstract
Like in any other semiconductor, point defects in transition-metal dichalcogenides (TMDs) are expected to strongly impact their electronic and optical properties. However, identifying defects in these layered two-dimensional materials has been quite challenging with controversial conclusions despite the extensive literature in the past decade. Using first-principles calculations, we revisit the role of chalcogen vacancies and hydrogen impurity in bulk TMDs, reporting formation energies and thermodynamic and optical transition levels. We show that the S vacancy can explain recently observed cathodoluminescence spectra of MoS2 flakes and predict similar optical levels in the other TMDs. In the case of the H impurity, we find it more stable sitting on an interstitial site in the Mo plane, acting as a shallow donor, and possibly explaining the often observed n-type conductivity in some TMDs. We also predict the frequencies of the local vibration modes for the H impurity, aiding its identification through Raman or infrared spectroscopy.
Voltage stability assessment of the power system using novel line voltage collapse index
Authors: Gupta Santosh Kumar , Mallik Sanjeev Kumar , Kumar Dhananjay , Kumar Shashi 
Published: May 2024

Abstract
Nowadays, for the maximum utilization of the power available, power systems are operated at their maximum stability limit due to the scarcity of natural resources. In this situation, quick monitoring and control of the power systems are very necessary for the electrical operators. This paper presents a novel line voltage stability index based on V-Q sensitivity. The index is created utilizing the network’s ABCD parameters and is based on an exact transmission system model. The new index is evaluated in terms of ABCD parameters from the reactive power equation of the power system. The proposed line index can predict the voltage collapse under heavy MVA loading, heavy reactive loading, randomly chosen heavy reactive loading, and different N-1 contingencies conditions. This has also the capability to predict voltage stability under different contingencies. The proposed method is compared with four existing methods named line stability index (Lmn), fast voltage stability index (FVSI), line stability factor (Lqp), and line voltage stability index (LVSI). Results show that the critical situation of the power system that has been investigated by the proposed approach is more accurate than these four existing methods under different operating scenarios. The accuracy and applicability of the proposed method are investigated on IEEE 14-bus and IEEE 118-bus systems.
Surface roughness estimation using vibration characteristics extracted by variational mode decomposition in turning
Authors: Guleria Vikrant , Kumar Vivek , Singh Pradeep K 
Published: May 2024

Abstract
This study presents an approach that combines variational mode decomposition (VMD) and relevance vector machine (RVM) as a prediction technique for surface roughness during turning. The method helps machinists detect irregularities during machining, such as looseness in machine parts or tool wear. The study uses work hardened EN8 steel and extracts vibration signal features into five modes. PSO optimized RVM prediction models are developed using these modes with and without combining cutting parameters. The most sensitive mode is selected for accurate surface roughness prediction. The results show that the first mode of decomposition when combined with cutting parameters provides the least mean square error of 0.1095. Surface roughness was found to be primarily influenced inversly by cutting speed and directly by feed rate respectively. The signal with high surface roughness value has high amplitude noise scattered over the large frequency range. The first decomposed mode of vibration signal increases noise with a large amplitude as surface roughness increases. The approach can be integrated into a microcontroller to regulate machine settings based on vibration data.