bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative Role of MDCT and FDG-PET/CT in the Diagnostic Evaluation of Mediastinal Mass Lesions: An Institutional Experience
Authors: Reddy Ravikanth 
Published: August 2022

Abstract
Background Mediastinal mass lesions span a wide histopathological and radiological spectrum. Partition of the mediastinum into specific compartments aids in differential diagnosis of mass lesions, assistance in biopsies, and other surgical procedures. Multidetector row computed tomography (MDCT) is a promising three-dimensional imaging tool allowing substantial anatomical volumes to be routinely covered with isotropic submillimeter spatial resolution to precisely localize lesions and biopsy needles for both benign and malignant disease lesions of the mediastinum.
Objective The aim of this study was to categorize mass lesions according to the mediastinal compartments to study their MDCT characteristics and to provide a comparative role of fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) in the diagnostic evaluation of mediastinal mass lesions.
Materials and Methods Patients with clinical or radiological suspicion of mediastinal lesions on the basis of an abnormal chest radiograph were referred to the department of radiodiagnosis at a tertiary care center between April 2015 and December 2019 for MDCT evaluation. A total of 80 cases were correlated with the histopathological diagnosis excluding aneurysms. Size, CT density (Hounsfield unit [HU] mean), and maximum standardized uptake value (SUVmax) of mediastinal and chest wall lesions were determined on FDG-PET/CT.
Results This study included a total of 102 cases, 72 males and 29 females. Mediastinal mass lesions were most common in the age group 46 to 60 years. Anterior mediastinum (n = 43, 42.2%) is the most commonly involved compartment followed by posterior mediastinum (n = 37, 35.9%) and middle mediastinum (n = 22, 21.8%). Transcompartmental involvement is more commonly seen involving the anterior and middle mediastinum. The SUVmax, HU mean, and size were higher in malignant cases (p = 0.001, p = 0.003, and p = 0.004, respectively). The current study found a cutoff value of 4.61 for SUVmax to discriminate benign lesions from malignant ones with a sensitivity and specificity of 73.7 and 75.9%, respectively (area under the curve: 0.841, 95% confidence interval: 0.793–0.965, p = 0.0001). The values of SUVmax and HU mean were higher in solid benign lesions than those of cystic benign lesions (p = 0.007 and p = 0.003, respectively).
Conclusion In the current study, MDCT has high diagnostic accuracy of ∼94% overall as compared with histopathology, and 97 and 92% for benign and malignant lesions, respectively, in the evaluation of mediastinal mass lesions. FDG-PET/CT may be complementary to conventional imaging methods for the evaluation of mediastinal and chest wall mass lesions. However, confirmatory tissue sampling is required to confirm PET positive findings for the definite diagnosis.
Epidemiology, Pathophysiology, and Management of Coronary Artery Disease in the Elderly
Authors: Fadah Kahtan , Hechanova Aimee , Mukherjee Debabrata 
Published: August 2022

AbstractElderly patients over the age of ≥ 75 years are especially susceptible to coronary artery disease (CAD) as age is an important nonmodifiable risk factors for atherosclerosis and a predictor of poorer outcomes. In fact, CAD is a major cause of mortality and morbidity in this population. Due to concerns of functional frailty, comorbidities, and patient preference of conservative to no treatment have played a role in reducing the interest in pursuing prospective studies in this high-risk group. In this review, we provide an overview of the epidemiology, pathophysiology, and management of CAD in older adults.
Review of Logic, Set Theory, and Isomorphism
Authors: Pereyra Nicolas A. 
Published: August 2022

The natural sciences are unavoidably a lead to incorporate numbers and, therefore, Mathematics. Mathematics, in turn, is based on the derivation or deduction of properties or propositions with respect to given objects or elements belonging to a given set. The process of derivation/deduction of properties/propositions is called logic. The general properties of elements and sets are called Set Theory. Two sets are considered isomorphic if one can establish a one-to-one relation between the two sets such that the corresponding operators and relations within each set are equivalent. In turn, real numbers can be defined and their general properties derived from the general properties of natural numbers through set theory and isomorphism.
In this chapter, we will present basic elements of logic, set theory, and isomorphism that we will be applying in the study of real exponential, logarithmic, and trigonometric functions.
Paradigm families in compounding
Authors: Cetnarowska Bozena 
Published: August 2022

Abstract
This chapter demonstrates the applicability of the notion of derivational paradigms and word-formation families to the study of compounds. Three families of English compounds are investigated which are headed by deverbal -er nominals. The semantic homogeneity of each of those compound families is assessed by analysing data from the Corpus of Contemporary American English (COCA), supplemented by some lexicographic searches and web searches. This involves the examination of the polysemy of the head nouns, the implicit semantic relation between compound elements and the transparency (or opacity) of the compounds which belong to the selected compound families. Comments are provided on the use of construction schemas to generalize over the internal structure and semantic interpretation of compound families (or subfamilies).
Paradigmatic aspects of deverbal noun conversion in English
Authors: Iordachioaia Gianina 
Published: August 2022

Abstract
In this paper, I seek to identify some recurrent and predictable patterns in the formation of deverbal converted nouns in English (to climb > the climb), which crucially differ from denominal conversion verbs (the bottle > to bottle) in showing only limited productivity. I will argue, however, that noun conversion exhibits regularities with respect to the morphological make-up and the semantic class of the base verbs, as well as to the noun’s interpretation in comparison to other competing suffix-based nominalizations, which I will describe as creating relatively stable derivational series within derivational paradigms (Hathout & Namer 2019).
Paradigms in English and Czech noun/verb conversion
Authors: Ševčíková Magda , Hledíková Hana 
Published: August 2022

Abstract
The study deals with English noun/verb conversion pairs that have both formally and semantically close counterpart pairs in Czech. The study’s aim is to examine how these nouns and verbs, linked with similar semantic relations in English and Czech, are accommodated in the two languages with different morphological structures and conversion playing a different role. The noun/verb pairs, extracted from the
British National Corpus
and from the SYN2000 corpus, are analysed as two-cell paradigms and examined along with selected derivatives. The data suggest that in the Czech sample, nominals are preferred over verbs in expressing the particular meanings and most verbs appear as denominal formations, often differently from their English counterparts.
Conversion in a paradigmatic framework of word formation
Authors: Soares Rodrigues Alexandra 
Published: August 2022

Abstract
This paper intends to present arguments that favour a paradigmatic approach to conversion, extending Bonami & Strnadová’s (2019) proposal of aligning relations within paradigmatic systems to the aligning relation criteria. The paper compares English and Portuguese conversion and syntactic nominalisations, according to the aligning relation criteria. Those criteria compare the different phenomena with affixed deverbal nouns situated in a paradigmatic level. A paradigmatic approach strengthens the concept of conversion as word formation because it enables us to observe an alignment between conversion pairs and affixation pairs, in contrast to syntactic nominalisations, which do not obey the same features of affixed deverbal nouns and are, thus, not aligned with them.
Structural and lexical aspects of the morphology of English participles
Authors: Fábregas Antonio 
Published: August 2022

Abstract
In this contribution, I explore the plausibility of a paradigm-free view to the analysis of different irregularities involving participles in English. I propose that making reference to paradigm-like entities is inescapable to provide a full account of the forms, but that the role of paradigms is more limited than standardly assumed in the literature. We will provide arguments in favour of the idea that most irregular participles (gone, been, written) emerge through the structurally-determined competition between stored verbal exponents. There will only be a small number of cases where it is necessary to invoke a higher-level object such as the paradigm, in the form of a diacritic (e.g., ABA cases such as come-came-come; Bauer et al. 2013).
English participles in the derivational paradigm
Authors: Popova Gergana 
Published: August 2022

Abstract
This chapter surveys the different uses of the English participles and discusses their status with respect to the distinction between derivation and inflection. In the debate about whether participles are verbal or adjectival, or indeed a mix between the two, most scholars have taken the position that ability to undergo further derivation (with affixes like -ness or negative un- for instance) indicates adjectival status. The paper assumes a descriptive focus and, without aiming to take a conclusive position relative to this general debate, explores such derivation further. The patterns covered in the paper are relatively few, but productive. This leads to derivational networks with sparse membership, but generally stable formal and semantic alignment.
Stable vs. variable eccentric load. Do they induce different training and physical performance outcomes?
Authors: Galiano Carlos , Floria Pablo , Muñoz‐López Alejandro , Sáez de Villarreal Eduardo , Nuñez Francisco Javier 
Published: August 2022

ABSTRACTSince most movements on the field require athletes to produce forces in variable and unpredictable contexts, the use of training programs based on identical repetitions of an exercise may not be optimal for movement transference. Therefore, the aim of this study was to analyse the effects of unexpected eccentric load variability during resistance training in team sport players. Sixty‐three men were randomly allocated to two experimental groups (Variable (VTG) and stable (STG) training group) and control group: (CG) volunteered to participate in this study. Experimental groups trained with the same average load of half‐squat exercise twice a week for six weeks using rotary inertial devices (RIDs) with (VTG) and without (STG) an unexpected variability of the load. The squat force was measured for every session with force plates. Counter‐movement jump (CMJ), sprint, and change of direction performances were measured pre and post‐test. CMJ performance improved for VTG (p = .014; ES = 0.7) and STG (p = .005; ES = 0.79) but not for CG. Exposure to high eccentric forces with RIDs lead athletes to improve physical performance in the trained force vector but, since RIDs induce in high levels of variability per se, increasing the level of variability of the exercise will not add benefits to physical performance and training outcomes.
A novel transfer learning fault diagnosis method for rolling bearing based on feature correlation matching
Authors: Wang Bo , Wang Baoqiang , Ning Yi 
Published: August 2022

Abstract
As one of the mainstream transfer learning methods, correlation alignment (CORAL) has been widely applied in fault diagnosis field and has achieved certain achievements. However, CORAL ignores the differences between domains in the matching process, which makes it difficult to measure the discrepancies between domains accurately. To compensate the shortcomings of the CORAL, this paper proposes a new feature correlation matching (FCM) method, and further it is applied as the objective function to propose a deep feature correlation matching network (DFCMN). The FCM method focuses on both first-order feature correlation and second-order feature correlation of the source and target domains, which measures the discrepancies between different domains more comprehensively and accurately. With the powerful feature mapping capability of neural network, the DFCMN can improve the feature similarity in different domain centers while reducing the discrepancies of feature distribution between different domains, so as to obtain more reliable shared features and improve the cross-work-conditions diagnosis accuracy. The effectiveness of the proposed method is verified through multiple transfer tasks utilizing public rolling bearing data sets.
Closely adjacent object segmentation based on periphery-restrictive region growing
Authors: Zhao Xinyue , Li Quanzhi , Zhang Meng , Wang Quanyou , He Zaixing , Lv Yongfeng 
Published: August 2022

Abstract
Closely adjacent objects are a kind of challenging scene in three-dimensional point cloud segmentation. To address this issue, we propose a novel periphery-restrictive region-growing-based segmentation method. First, the clouds are smoothed by the moving least squares method and the periphery of the target clouds is extracted. Then an initial seed generation based on minimum curvature first of non-periphery points, namely, non-periphery seed generation algorithm is proposed. Finally, a nearest periphery restrictive growing algorithm is proposed for accurate segmentation. In addition, we establish a point cloud dataset of adjacent objects which contains three typically adjacent objects on the pipeline. We evaluate the effectiveness and accuracy of the proposed method on this dataset, and the extensive experiments show that the proposed method performs well on closely adjacent objects.
An analysis of detectable leakage rate for oil pipelines based on acoustic wave method
Authors: Lang Xianming , Zhu Yongqiang 
Published: August 2022

Abstract
Oil pipeline leakage will not only cause economic losses, but also pollute the environment, so the leakage detection of pipelines is very important. The acoustic wave method is widely used in pipeline leak detection, and the leak acoustic signal collected by the acoustic wave sensor often contains a lot of noise, which makes it impossible to accurately determine the inflection point of the signal curve and reduces the accuracy of pipeline leak detection. This paper proposes a denoising algorithm based on mutual information optimization complete ensemble empirical mode decomposition with adaptive noise combined with cross-spectral analysis. Compared with other methods, this method can accurately select the effective intrinsic modal function for signal reconstruction, the denoising effect is more obvious, and the original information is preserved to a greater extent. Acoustic waves are attenuated during the propagation process, and will be affected by factors such as pipe connection ports and elbows, making it impossible to accurately determine the amplitude of acoustic waves around the pipeline. According to the propagation characteristics of acoustic waves and various factors that affect the propagation of acoustic waves, this paper establishes a model for calculating the amplitude of acoustic waves, which can accurately determine the amplitude of acoustic waves everywhere in the pipeline. Finally, according to the model, the relationship between pipeline characteristics and detectable leakage rate is analysed. Field experiments show that the proposed model is accurate and the denoising algorithm is efficient. The minimum detectable leakage rate of the oil pipeline can reach 0.43% when the acoustic wave method is used for leak detection.
Domain knowledge driven 3D dose prediction using moment-based loss function
Authors: Jhanwar Gourav , Dahiya Navdeep , Ghahremani Parmida , Zarepisheh Masoud , Nadeem Saad 
Published: August 2022

Abstract

Objective. To propose a novel moment-based loss function for predicting 3D dose distribution for the challenging conventional lung intensity modulated radiation therapy plans. The moment-based loss function is convex and differentiable and can easily incorporate clinical dose volume histogram (DVH) domain knowledge in any deep learning (DL) framework without computational overhead. Approach. We used a large dataset of 360 (240 for training, 50 for validation and 70 for testing) conventional lung patients with 2 Gy × 30 fractions to train the DL model using clinically treated plans at our institution. We trained a UNet like convolutional neural network architecture using computed tomography, planning target volume and organ-at-risk contours as input to infer corresponding voxel-wise 3D dose distribution. We evaluated three different loss functions: (1) the popular mean absolute error (MAE) loss, (2) the recently developed MAE + DVH loss, and (3) the proposed MAE + moments loss. The quality of the predictions was compared using different DVH metrics as well as dose-score and DVH-score, recently introduced by the AAPM knowledge-based planning grand challenge. Main results. Model with (MAE + moment) loss function outperformed the model with MAE loss by significantly improving the DVH-score (11%, p < 0.01) while having similar computational cost. It also outperformed the model trained with (MAE + DVH) by significantly improving the computational cost (48%) and the DVH-score (8%, p < 0.01). Significance. DVH metrics are widely accepted evaluation criteria in the clinic. However, incorporating them into the 3D dose prediction model is challenging due to their non-convexity and non-differentiability. Moments provide a mathematically rigorous and computationally efficient way to incorporate DVH information in any DL architecture. The code, pretrained models, docker container, and Google Colab project along with a sample dataset are available on our DoseRTX GitHub (https://github.com/nadeemlab/DoseRTX)
Simple analytical models and analysis of bistable vibration energy harvesters
Authors: Morel Adrien , Charleux Ludovic , Demouron Quentin , Benhemou Aya , Gibus David , Saint-Martin Camille , Carré Aurélien , Roux Émile , Huguet Thomas , Badel Adrien 
Published: August 2022

Abstract
In order to scavenge the energy of ambient vibrations, bistable vibration energy harvesters constitute a promising solution due to their large frequency bandwidth. Because of their complex dynamics, simple models that easily explain and predict the behavior of such harvesters are missing from the literature. To tackle this issue, this paper derives simple analytical closed-form models of the characteristics of bistable energy harvesters (e.g. power-frequency response, displacement response, cut-off frequency of the interwell motion) by mean of truncated harmonic balance methods. Measurements on a bistable piezoelectric energy harvester illustrate that the proposed analytical models allow the prediction of the mechanical displacement and harvested power, with a relative error below 10%. From these models, the influences of various parameters such as the inertial mass, the acceleration amplitude, the electromechanical coupling, and the resistive load, are derived, analyzed and discussed. The proposed models and analysis give an intuitive understanding of the dynamics of bistable vibration energy harvesters, and can be exploited for their design and optimization.
All optical logic gates function by ring resonator properties aiding photonic crystal
Authors: Elhachemi Kouddad , Vigneswaran D , Rafah Naoum , Koundal Deepika , Leila Dekkiche 
Published: August 2022

Abstract
Optical logic gates based on the Pockels effect are key components of light-wave communication networks and quantum computing because they are highly efficient and ultrafast. In this paper, we proposed a new hybrid platform of gallium arsenide and barium titanate (GaAs-BTO) for Ultraefficient Electro-Optic Tuning based on two-dimensional photonic crystals, the only proposed multifunctional structure is used to realize various very high-performance photonic logic gates such as BUFFER, NOT, AND, NAND, NOR, OR, XOR, XNOR. The functional parameters of these miniature logic gates are analyzed and optimized numerically by the FDTD method. The simulation results show that the contrast ratio is very high, with a very small footprint of 157 μm2, the response time is ultrafast 1 ps which corresponds to a bit rate of 1 Tbps.
An effective fluid description of scalar-vector-tensor theories under the sub-horizon and quasi-static approximations
Authors: Cardona Wilmar , Orjuela-Quintana J. Bayron , Valenzuela-Toledo César A. 
Published: August 2022

AbstractWe consider scalar-vector-tensor (SVT) theories with second-order equations of motion and tensor propagation speed equivalent to the speed of light. Under the sub-horizon and the quasi-static approximations we find analytical formulae for an effective dark energy fluid, i.e., sound speed, anisotropic stress as well as energy density and pressure. We took advantage of our general, analytical fluid description and showed that it is possible to design SVT cosmological models which are degenerate with ΛCDM at the background level while having gravity strengthGeff<GNat late-times as well as non-vanishing dark energy perturbations. We implemented SVT designer models in the widely used Boltzmann solverCLASSthus making it possible to test SVT models against astrophysical observations. Our effective fluid approach to SVT models reveals non trivial behaviour in the sound speed and the anisotropic stress well worth an investigation in light of current discrepancies in cosmological parameters such asH0andσ8.
Type A uncertainty analysis validation of type B analysis for three-axis accelerometer calibrations
Authors: Geist Jon , Gaitan Michael 
Published: August 2022

Abstract
A type-A uncertainty analysis of the magnitude of the local gravitational field can be used to validate type-B uncertainty estimates of calibrations of triaxial accelerometers by rotation in the gravitational field. We demonstrate the application of this method to validate a type-B uncertainty estimate at the sub 0.1% level of the errors introduced by a high-accuracy, two-axis, accelerometer-characterization system.
Core radiative collapse characterisation and integrated modelling in WEST plasmas
Authors: Ostuni V. , Morales J. , Artaud J.-F. , Bourdelle C. , Manas P. , Fedorczak N. , Dumont R. , Goniche M. , Maget P. , Peysson Y. , the WEST Team  
Published: August 2022

Abstract
In the full tungsten environment of WEST, during its first phase of operation, around 25% of the pulses exhibited a rapid central electron temperature collapse. In its first phase, WEST plasmas were mostly heated by lower hybrid current drive (LHCD) and ion cyclotron resonance heating (ICRH). In this publication, the collapsing pulses are analysed to understand the key actuators at play. Experimentally, an initial slow reduction of central electron temperature due to a density increase is observed, while the central tungsten profile is flat and constant in time. Then, radiative collapse occurs: the core tungsten profile peaks rapidly, at the same time, the central hard x-ray channel measurement decreases indicating a change in core LHCD absorption. Integrated modelling is used to explore the causality chain. To capture the collapse speed, both, tungsten core peaking and reduction of central LHCD absorption are required. When central LHCD power absorption is reduced, core electron and ion temperature profiles flatten which reduces the tungsten neoclassical thermal screening and leads to the observed core tungsten accumulation.