bluuebunny/crossref_metadata_2025 huggingface dataset:
An analysis of detectable leakage rate for oil pipelines based on acoustic wave method
Authors: Lang Xianming , Zhu Yongqiang
Published: August 2022

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

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

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

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

We 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.
Learnable three-dimensional Gabor convolutional network with global affinity attention for hyperspectral image classification
Authors: Pan Hai-Zhu , Liu Mo-Qi , Ge Hai-Miao , Yuan Qi
Published: August 2022

Benefiting from the development of hyperspectral imaging technology, hyperspectral image (HSI) classification has become a valuable direction in remote sensing image processing. Recently, researchers have found a connection between convolutional neural networks (CNNs) and Gabor filters. Therefore, some Gabor-based CNN methods have been proposed for HSI classification. However, most Gabor-based CNN methods still manually generate Gabor filters whose parameters are empirically set and remain unchanged during the CNN learning process. Moreover, these methods require patch cubes as network inputs. Such patch cubes may contain interference pixels, which will negatively affect the classification results. To address these problems, in this paper, we propose a learnable three-dimensional (3D) Gabor convolutional network with global affinity attention for HSI classification. More precisely, the learnable 3D Gabor convolution kernel is constructed by the 3D Gabor filter, which can be learned and updated during the training process. Furthermore, spatial and spectral global affinity attention modules are introduced to capture more discriminative features between spatial locations and spectral bands in the patch cube, thus alleviating the interfering pixels problem. Experimental results on three well-known HSI datasets (including two natural crop scenarios and one urban scenario) have demonstrated that the proposed network can achieve powerful classification performance and outperforms widely used machine-learning-based and deep-learning-based methods.
Theoretical study of the enhancement of saturable absorption of Kr under x-ray free-electron laser
Authors: Ye Jiaxin , Yang Yixuan , Yang Chen , Jiang Gang
Published: August 2022

The generation of hollow atoms will reduce the probability of light absorption and provide a high-quality diffraction image in the experiment. In this paper, we calculated the ionization rate of the Kr atom under x-ray free-electron laser (XFEL) using Hartree–Fock–Slater model and simulated the ionization model of Kr atom using Monte–Carlo method to determine the response of the hollow atom of Kr atom to the XFEL photon energy. Calculating the correlation between the total photoionization cross-section of the ground state of Kr atom and the photon energy, we determined three particular photon energies of 1.75 keV, 1.90 keV, and 14.30 keV. The dynamics simulation under the experimental condition’s 17.50 keV photon energy was achieved by implementing the Monte–Carlo method and calibrating the photon flux modeling parameters. Consequently, our calculated data are more consistent with experimental phenomena than previous theoretical studies. The saturable absorption of Kr at 1.75 keV, 1.90 keV, 14.30 keV, and 17.50 keV energies was further investigated by using the optimized photon flux model theory. We compared the statistics on main ionization paths under those four specific photon energies and calculated the population changes of various Kr hollow atoms with different configurations. The results demonstrate that the population of hollow atoms produced at the critical ionization photon energy is high. Furthermore, the change of population with respect to position is smooth, which shows a significant difference between the generation mode of ions with low and high photon energies. The result is important for the study of medium- and high-Z element hollow atoms, which has substantial implications for the study of hollow atoms with medium and high charge states, as well as for the scaling of photon energy of free electron lasers.
A color image encryption algorithm based on hyperchaotic map and DNA mutation
Authors: Gao Xinyu , Sun Bo , Cao Yinghong , Banerjee Santo , Mou Jun
Published: August 2022

We devise a color image encryption scheme via combining hyperchaotic map, cross-plane operation and gene theory. First, the hyperchaotic map used in the encryption scheme is analyzed and studied. On the basis of the dynamics of hyperchaotic map, a color image encryption scheme is designed. At the end of the encryption process, a DNA mutation operation is used to increase the encoding images’ randomness and to improve the encryption algorithm’s security. Finally, simulation experiments, performance analysis, and attack tests are performed to prove the effectiveness and security of the designed algorithm. This work provides the possibility of applying chaos theory and gene theory in image encryption.
Type A uncertainty analysis validation of type B analysis for three-axis accelerometer calibrations
Authors: Geist Jon , Gaitan Michael
Published: August 2022

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

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.
The effective noise of stochastic gradient descent
Authors: Mignacco Francesca , Urbani Pierfrancesco
Published: August 2022

Stochastic gradient descent (SGD) is the workhorse algorithm of deep learning technology. At each step of the training phase, a mini batch of samples is drawn from the training dataset and the weights of the neural network are adjusted according to the performance on this specific subset of examples. The mini-batch sampling procedure introduces a stochastic dynamics to the gradient descent, with a non-trivial state-dependent noise. We characterize the stochasticity of SGD and a recently-introduced variant, persistent SGD, in a prototypical neural network model. In the under-parametrized regime, where the final training error is positive, the SGD dynamics reaches a stationary state and we define an effective temperature from the fluctuation–dissipation theorem, computed from dynamical mean-field theory. We use the effective temperature to quantify the magnitude of the SGD noise as a function of the problem parameters. In the over-parametrized regime, where the training error vanishes, we measure the noise magnitude of SGD by computing the average distance between two replicas of the system with the same initialization and two different realizations of SGD noise. We find that the two noise measures behave similarly as a function of the problem parameters. Moreover, we observe that noisier algorithms lead to wider decision boundaries of the corresponding constraint satisfaction problem.
Approximate method for helical particle trajectory reconstruction in high energy physics experiments
Authors: Topolnicki K. , Bold T.
Published: August 2022

High energy physics experiments, in particular experiments
at the LHC, require the reconstruction of charged particle
trajectories. Methods of reconstructing such trajectories have been
known for decades, yet the applications at High Luminosity LHC
require this reconstruction to be fast enough to be suitable for
online event filtering.

A particle traversing the detector volume leaves signals in active
detector elements from which the trajectory is reconstructed. If the
detector is submerged in a uniform magnetic field that trajectory is
approximately helical. Since a collision event results in the
production of many particles, especially at high luminosities, the
first phase of trajectory reconstruction is the formation of
candidate trajectories composed of a small subset of detector
measurements that are then subject of resource intensive precise
track parameters estimation.

In this paper, we suggest a new approach that could be used to
perform this classification. The proposed procedure utilizes the z 
coordinate in the longitudinal direction in addition to the x, y 
coordinates in the plane perpendicular to the direction of the
magnetic field. The suggested algorithm works equally well for
helical trajectories with different proximities to the beamline
which is beneficial when searching for products of particles with
longer lifetimes.
Predicting electricity infrastructure induced wildfire risk in California
Authors: Yao Mengqi , Bharadwaj Meghana , Zhang Zheng , Jin Baihong , Callaway Duncan S
Published: August 2022

This paper examines the use of risk models to predict the timing and location of wildfires caused by electricity infrastructure. Our data include historical ignition and wire-down points triggered by grid infrastructure collected between 2015–2019 in Pacific Gas & Electricity territory along with various weather, vegetation, and very high resolution data on grid infrastructure including location, age, and materials. With these data we explore a range of machine learning methods and strategies to manage training data imbalance. The best area under the receiver operating characteristic we obtain is 0.776 for distribution feeder ignitions and 0.824 for transmission line wire-down events, both using the histogram-based gradient boosting tree algorithm with under-sampling. We then use these models to identify which information provides the most predictive value. After line length, we find that weather and vegetation features dominate the list of top important features for ignition or wire-down risk. Distribution ignition models show more dependence on slow-varying vegetation variables such as burn index, energy release content, and tree height, whereas transmission wire-down models rely more on primary weather variables such as wind speed and precipitation. These results point to the importance of improved vegetation modeling for feeder ignition risk models, and improved weather forecasting for transmission wire-down models. We observe that infrastructure features make small but meaningful improvements to risk model predictive power.
Equivalence of mean-field avalanches and branching diffusions: from the Brownian force model to the super-Brownian motion
Authors: Le Doussal Pierre
Published: August 2022

We point out that the mean-field theory of avalanches in the dynamics of elastic interfaces, the so-called Brownian force model (BFM) developed recently in non-equilibrium statistical physics, is equivalent to the so-called super-Brownian motion (SBM) developed in probability theory, a continuum limit of branching processes related to space-embedded Galton–Watson trees. In particular the exact solvability property recently (re-)discovered from the field theory in mean-field avalanches (the ‘instanton equation’) maps onto the so-called Dawson–Watanabe 1968 duality property. In the light of this correspondence we compare the results obtained independently in the two fields, and transport some of them from one field to the other. In particular, we discuss a scaling limit of the branching Brownian motion which maps onto the continuum field theory of mean-field avalanches.
Lax equations for relativistic

GL(NM,C)

Gaudin models on elliptic curve
Authors: Trunina E , Zotov A
Published: August 2022

We describe the most general GL
NM
classical elliptic finite-dimensional integrable system, which Lax matrix has n simple poles on elliptic curve. For M = 1 it reproduces the classical inhomogeneous spin chain, for N = 1 it is the Gaudin type (multispin) extension of the spin Ruijsenaars–Schneider model, and for n = 1 the model of M interacting relativistic GL
N
tops emerges in some particular case. In this way we present a classification for relativistic Gaudin models on GL-bundles over elliptic curve. As a by-product we describe the inhomogeneous Ruijsenaars chain. We show that this model can be considered as a particular case of multispin Ruijsenaars–Schneider model when residues of the Lax matrix are of rank one. An explicit parametrization of the classical spin variables through the canonical variables is obtained for this model. Finally, the most general GL
NM
model is also described through R-matrices satisfying associative Yang–Baxter equation. This description provides the trigonometric and rational analogues of GL
NM
models.
A high-sensitivity rapid acquisition spectrometer for lanthanide(III) luminescence
Authors: Nawrocki Patrick R , Nielsen Villads R M , Sørensen Thomas Just
Published: August 2022

Detecting luminescence beyond 750–800 nm becomes problematic as most conventional detectors are less sensitive in this range, and as simple corrections stops being accurate. Lanthanide luminescence occurs in narrow bands across the spectrum from 350–2000 nm. The most emissive lanthanide(III) ions have bands from 450 nm to 850 nm, some with additional bands in the NIR. Investigating NIR bands are hard, but the difficulties already start at 700 nm. In general, the photon flux from lanthanide(III) emitters is not great, and the bands beyond 700 nm are very weak, we therefore decided to build a spectrometer based on cameras for microscopy with single-photon detection capabilities. This was found to allieviate all limitations and to allow for fast and efficient recording of luminescence spectra in the range from 450 to 950 nm. The spectrometer characteristics were investigated and the performance was benchmarked against two commercial spectrometers. We conclude that this spectrometer is ideal for investigating lanthanide luminescence, and all other emitters with emission in the target range.
Investigation of physical properties of Fe3O4/Au-Ag@MoS2 nanoparticles on heat distribution in cancerous liver tissue
Authors: Seyedjamali Tina , Farahzadi Mohamadreza Kazem , Arabi Hossein
Published: August 2022

Liver cancer has significantly grown in recent years, and thus its mortality rate has also increased since its symptoms appear to be in malignant stages and the treatment path at this stage is extremely challenging. New therapies based on producing heat in cancerous tissues have opened up a new way to treat cancer. This study investigated the treatment of liver cancer by the magnetic hyperthermia approach and nanoparticles (NPs) such as iron oxide (

F

e

3

O

4

) core with gold (Au), silver (Ag) alloy shell, and molybdenum disulfide (

M
o

S

2

) coating. The optical properties of these NPs within the tumor, including the extinction coefficient and surface plasmon peak (SPR) as a function of size, structure, different compositions, and thickness, were also examined using the effective medium theory, followed by assessing the impact of temperature distribution through the analytical modeling of an alternating current magnetic field. The results demonstrated that NPs with a compound of

F

e

3

O

4

−
A

u

0.25

A

g

0.75

@
M
o

S

2

,

a 3 nm thick cover of Au-Ag alloy, and two layers of

M
o

S

2

have the best coefficient of extinction and SPR in the biological window. The Au-Ag alloy improved the extinction coefficient and simultaneously prevented the accumulation of magnetic NPs. Considering that the Au-Ag alloy alone cannot function within the range of biological windows,

M
o

S

2

was used, which increased the extinction efficiency at higher wavelengths. The examination of the temperature distribution in the tumor for the proposed alloy compound indicated that after a short time from irradiation initiation, the tumor temperature reaches 45 °C. Further, the temperature distribution within the tumor tissue reached its maximum value at the center of the tumor and decreased dramatically while getting away from the center. Finally, the use of magnetic hyperthermia enabled localized delivery of therapeutic doses to malignant tumors, thereby representing superior performance and efficiency over the photothermal method.
Negative refractive index modified fishnet enhancement by wire shift
Authors: Wegrowski Antoine , Wang Wei-Chih , Tsui Chileung , Garu Prabir
Published: August 2022

We propose a modification to the negative refractive index fishnet design and demonstrate numerically that this modification leads to an even lower refractive index resonance peak and higher gains compared to the fishnet design, this effect being sustained for design dimensions ranging from the nanometer up to the millimeter and for various materials. This modification, we called ‘bd design’, consists in a shift of the metallic arms to the extremities of the metallic slab, the structure remaining otherwise identical. We discuss the numerical comparison between the use of the fishnet design and the bd design, simulating three fishnet-based metamaterials presented in the literature and showing how a modification of these metamaterials to the bd design leads to improved performances. Finally, we present an explanation for the superior characteristics of the bd design.
Optimisation of additives on the performance of loess/fly ash-based ceramic membrane supports
Authors: Tong Zhi , Wang Han , Yang Xiaoyu , Cui Shuangke , Zhang Jianxu
Published: August 2022

Inorganic ceramic membranes have received a lot of attention due to their resistance to acid and alkali corrosion and ease of cleaning and utilisation, however, their high cost has limited their widespread use. To obtain lower-cost ceramic membranes with better performance, in this paper, single-channel tubular ceramic membrane supports were prepared using natural loess and solid waste fly ash as raw materials. This paper firstly investigated the effects of various additives (including carboxymethyl cellulose (CMC), graphite, calcium carbonate, copper oxide, magnesium oxide, and manganese dioxide,) on the pore size distribution, pure water flux, and flexural strength of the supports to select the appropriate additives; secondly, the response surface methodology was used to determine the amount of each parameter to be added. The results showed that CMC was more viscous and malleable compared to graphite and CaCO3, thus increasing the density and pure water flux of the supports. MnO2 improved both the pure water flux and flexural strength of the supports compared to CuO and MgO. The best sample was obtained when the contents of CMC, MnO2, and kaolinite were 9.85 wt%, 10.62 wt%, and 4.8 wt%, respectively, the best sample obtained exhibited a pure water flux of 4985.52 L·m−2·h−1·MPa−1 and a flexural strength of 45.4 MPa. The support obtained meets the conditions for the application of porous ceramic carriers and provides a viable pathway for the wide application of low-cost ceramic membrane carriers.
Flexibility of fluorinated graphene based memristor structures: current flow model in a multi-barrier system under tensile strain
Authors: Ivanov A I , Antonova I V
Published: August 2022

The flexibility of two types of memristor structures with fluorinated graphene (FG) based active layers (FG with graphene islands on polyvinyl alcohol, FG/PVA, and films from nanoparticles of V2O5 capsulated with FG, FG/V2O5) under the tensile strain in bending conditions was investigated and compared in the present study. Both types of memristors show a similar mechanism of resistance switchings (current paths on traps without filaments). Multi-barrier model of current flow was used to estimate the barrier parameters connected to FG from experiments on resistive switching of memristor structures in the bending condition. The first type of structures (Ag/FG/PVA/Ag) demonstrates the record high values of flexibility: ON/OFF current relation is not changed up to 7% tensile strain created by bending. The second type of structures (Gr/FG/V2O5/Gr with graphene contacts) show a decrease in ON current already for tensile strain more than 2%. The similar mechanism of current flow allows us to use the similar theory for description of the current flow versus the tensile strain. In spite of different structures and morphology of memristors, the typical values of the barrier height extracted from the theoretical description were similar: ∼1.5 eV with an effective barrier thickness of ∼16.5 nm and ∼1.3–1.6 eV with thickness 13.5–15.0 nm for FG/PVA and FG/V2O5 structures, respectively. Increase in the barrier thickness over 19 nm in both cases leads to the strong decrease in ON current of memristors.
Implementation and analysis of 32 channel MDRZ DWDM system at narrow channel spacing
Authors: Dhadhal Dharmendra , Mishra Vivekanand , Thummar Ruturaj
Published: August 2022

This work is proposed to examine modified duobinary return to zero modulation in DWDM long haul communication system. In this framework we simulate 32 channels each channel data rate is 40 Gbps multiplexed with the channel spacing 80 GHz, 90 GHz and 100 GHz to perceive 1.2 Tbps data. This data completed transmission Distance over 250 KM by utilizing scattering remuneration strategy. This 40 Gbps data is encoded by utilizing Mach Zehnder modulator (MRZ) inferred by CW laser of power − 10 dBm, − 5 dBm, 0 dBm, 5 dBm, 10 dBm. In the system analysis, we use modified duobinary return to zero (MDRZ) in the DWDM communication long haul system.
Corrugated nanowires as distributed Bragg reflectors
Authors: Wilson D P , LaPierre R R
Published: August 2022

Distributed Bragg reflectors (DBRs), comprised of periodic refractive index changes, are widely used in optoelectronic devices as resonators, filters and sensors. The heterostructures required for DBRs can be difficult to implement in nanostructures due to poor compositional control on the nanoscale. In the present paper, simulation results are presented of the reflectance spectra from DBR structures that are implemented using periodic perturbations of a nanowire (NW) diameter, rather than heterostructures. The corrugated NW structure can produce a DBR stopband with reflectance near unity. The Bragg wavelength and stopband can be tuned by adjusting the pitch of the nanowire arrays, the corrugation depth, and the period of the corrugation. The proposed DBR structure presents a new paradigm for a wide range of nanoscale device applications.
Exploring Teacher Caring as a “Happy Object” in Language Teacher Accounts of Happiness
Authors: Miller Elizabeth R , Gkonou Christina
Published: August 2022

This article explores how the language teachers in our study associated particular teaching experiences with feeling happy in qualitative interview accounts. Adopting a critical poststructural orientation, it uses the concept of sticky objects (Ahmed 2010; Benesch 2017) to explore how contexts, social discourses, relationships and emotional norms are entangled in and shape emotions such as happiness. More particularly, it adopts Ahmed’s (2010) notion of “happy objects” in exploring language teachers’ associations of “teacher caring” with feeling happy. Rather than exploring what happiness is, this study investigates what happiness does to and for language teachers, focusing on their accounts of teacher caring. It argues that the happy object of teacher caring is enmeshed in normative discourses that cast individual teachers as responsible for caring enough in order to help their students to succeed as determined by institutional norms of student achievement. Ultimately, it contends that accounts of teacher happiness require careful scrutiny for what they can tell us about the complex intersections of emotions with normative discourses, structures and values.
Habitat change alters the expression and efficiency of a female ornament
Authors: Bäckroos Sini , Ala-Ilomäki Lea , Candolin Ulrika
Published: August 2022

Anthropogenic habitat changes are disrupting the mate choice process in a range of organisms, with consequences for populations and communities. Research has so far focused on male sexually selected traits and female mate choice, given their conspicuousness, whereas effects on female ornaments and male mate choice have been largely overlooked. Yet, females of many species develop ornaments that males use in mate choice. These ornaments can be costly and reduce female fecundity and viability and, hence, influence population growth rate. Thus, attention should be paid to changes in female ornaments and the consequences the changes have for populations. Here, we show that declining visibility in aquatic ecosystems reduces the investment of female three-spined stickleback in a melanin-based ornament in favor of increased mate search activity. The adjustment appears adaptive as males pay less attention to the ornament under poor visibility, and as melanin-based ornaments are generally physiologically costly. It is likely that past fluctuations in visibility have promoted the evolution of environment-dependent plasticity in female ornamentation. More attention should be paid to changes in female ornaments and their adaptive value, across taxa, given the impact that female investment in ornaments can have on fecundity and population growth rate. Environments are changing at an accelerating rate because of human activities and knowledge of the responses of both males and females is needed to evaluate and predict the ultimate impact on populations and biodiversity.
Identifying the kind behind SMILES—anatomical therapeutic chemical classification using structure-only representations
Authors: Cao Yi , Yang Zhen-Qun , Zhang Xu-Lu , Fan Wenqi , Wang Yaowei , Shen Jiajun , Wei Dong-Qing , Li Qing , Wei Xiao-Yong
Published: August 2022

Anatomical Therapeutic Chemical (ATC) classification for compounds/drugs plays an important role in drug development and basic research. However, previous methods depend on interactions extracted from STITCH dataset which may make it depend on lab experiments. We present a pilot study to explore the possibility of conducting the ATC prediction solely based on the molecular structures. The motivation is to eliminate the reliance on the costly lab experiments so that the characteristics of a drug can be pre-assessed for better decision-making and effort-saving before the actual development. To this end, we construct a new benchmark consisting of 4545 compounds which is with larger scale than the one used in previous study. A light-weight prediction model is proposed. The model is with better explainability in the sense that it is consists of a straightforward tokenization that extracts and embeds statistically and physicochemically meaningful tokens, and a deep network backed by a set of pyramid kernels to capture multi-resolution chemical structural characteristics. Its efficacy has been validated in the experiments where it outperforms the state-of-the-art methods by 15.53% in accuracy and by 69.66% in terms of efficiency. We make the benchmark dataset, source code and web server open to ease the reproduction of this study.
Ferumoxytol dynamic contrast enhanced magnetic resonance imaging identifies altered placental cotyledon perfusion in rhesus macaques
Authors: Seiter Daniel P , Nguyen Sydney M , Morgan Terry K , Mao Lu , Dudley Dawn M , O’connor David H , Murphy Megan E , Ludwig Kai D , Chen Ruiming , Dhyani Archana , Zhu Ante , Schotzko Michele L , Brunner Kevin G , Shah Dinesh M , Johnson Kevin M , Golos Thaddeus G , Wieben Oliver
Published: August 2022

Identification of placental dysfunction in early pregnancy with noninvasive imaging could be a valuable tool for assessing maternal and fetal risk. Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) can be a powerful tool for interrogating placenta health. After inoculation with Zika virus or sham inoculation at gestation age (GA) 45 or 55 days, animals were imaged up to three times at GA65, GA100, and GA145. DCE MRI images were acquired at all imaging sessions using ferumoxytol, an iron nanoparticle-based contrast agent, and analyzed for placental intervillous blood flow, number of perfusion domains, and perfusion domain volume. Cesarean section was performed at GA155, and the placenta was photographed and dissected for histopathology. Photographs were used to align cotyledons with estimated perfusion domains from MRI, allowing comparison of estimated cotyledon volume to pathology. Monkeys were separated into high and low pathology groups based on the average number of pathologies present in the placenta. Perfusion domain flow, volume, and number increased through gestation, and total blood flow increased with gestation for both low pathology and high pathology groups. A statistically significant decrease in perfusion domain volume associated with pathology was detected at all gestational ages. Individual perfusion domain flow comparisons demonstrated a statistically significant decrease with pathology at GA100 and GA145, but not GA65. Since ferumoxytol is currently used to treat anemia during human pregnancy and as an off-label MRI contrast agent, future transition of this work to human pregnancy may be possible.
Improving the transition capability of the low-voltage wind turbine in the sub-synchronous state using a fuzzy controller
Authors: Dwijendra Ngakan Ketut Acwin , Jalil Abduladheem Turki , Abed Azher M , Bashar Bashar S , Al-Nussairi Ahmed Kateb Jumaah , Hammid Ali Thaeer , Shamel Ali , Uktamov Khusniddin Fakhriddinovich
Published: August 2022

The main problem of wind turbines is associated with induction generators in their power supply during short circuits in the grid. In this research, a new method is presented for the uninterrupted operation of a wind turbine equipped with an induction generator fed on both sides of feeding during network errors. Wind farms equipped with a doubly-fed induction generator (DFIG) require two abilities to allow system operators to increase proficiency. These capabilities include fault ride-through and synchronization of output force fluctuations, especially when these generators generate significant electrical power. A MATLAB® software environment has been used to evaluate and improve the performance of these turbines. A fuzzy complement (FC) controller is used to improve the performance of the DFIG. The results demonstrate that this controller limits the operation of the turbine current and voltage in the short-circuit mode well. Regarding results obtained from comparing two different modes, it can be said that ripple is 4% in the FC mode, while this parameter is equal to 10% for the proportional-integral controller.
Regional variation in tolvaptan prescribing across England: national data and retrospective evaluation from an expert centre
Authors: Chong Jiehan , Harris Tess , Ong Albert C M
Published: August 2022

Background

Tolvaptan, a vasopressin V2 receptor antagonist, was approved in 2015 by the UK National Institute for Health and Care Excellence for use in patients with autosomal dominant polycystic kidney disease (ADPKD) and rapid disease progression. Simultaneous guidance was issued by the UK Kidney Association (UKKA) to facilitate national implementation.

Methods

Data on tolvaptan prescribing in England was obtained through the National Health Service (NHS) Digital, a national survey of all 77 adult kidney units, and the implementation of UKKA guidance was evaluated at an expert PKD centre.

Results

A regional variation of up to 4-fold for tolvaptan prescribing in England was found. Despite most kidney units following UKKA guidance, centre-based estimates of eligible or treated patient numbers were highly variable. Retrospective evaluation at an expert PKD centre revealed that in a cohort demonstrating rapid estimated glomerular filtration rate (eGFR) decline, 14% would not be eligible for tolvaptan by Mayo imaging classification and more than half (57%) would not be eligible by Predicting Renal Outcome in Polycystic Kidney Disease score. The 3-year discontinuation rate was higher than expected (56%), the majority (70%) due to aquaretic symptoms. In patients taking tolvaptan for at least 2 years, 81% showed a reduction in the rate of eGFR decline compared with baseline, with earlier disease associated with positive treatment response.

Conclusion

Real-world data have revealed a much higher regional variation in tolvaptan prescribing for ADPKD in England than expected. We propose further investigation into the factors responsible for this variation.
Pushed Northward by Climate Change: Range Shifts With a Chance of Co-occurrence Reshuffling in the Forecast for Northern European Odonates
Authors: Pélissié Mathieu , Johansson Frank , Hyseni Chaz
Published: August 2022

Biodiversity is heavily influenced by ongoing climate change, which often results in species undergoing range shifts, either poleward or uphill. Range shifts can occur provided suitable habitats exist within reach. However, poleward latitudinal shifts might be limited by additional abiotic or biotic constraints, such as increased seasonality, photoperiod patterns, and species interactions. To gain insight into the dynamics of insect range shifts at high latitudes, we constructed ecological niche models (ENMs) for 57 Odonata species occurring in northern Europe. We used citizen science data from Sweden and present-day climatic variables covering a latitudinal range of 1,575 km. Then, to measure changes in range and interactions among Odonata species, we projected the ENMs up to the year 2080. We also estimated potential changes in species interactions using niche overlap and co-occurrence patterns. We found that most Odonata species are predicted to expand their range northward. The average latitudinal shift is expected to reach 1.83 and 3.25 km y−1 under RCP4.5 and RCP8.5 scenarios, respectively, by 2061–2080. While the most warm-dwelling species may increase their range, our results indicate that cold-dwelling species will experience range contractions. The present-day niche overlap patterns among species will remain largely the same in the future. However, our results predict changes in co-occurrence patterns, with many species pairs showing increased co-occurrence, while others will no longer co-occur because of the range contractions. In sum, our ENM results suggest that species assemblages of Odonata—and perhaps insects in general—in northern latitudes will experience great compositional changes.
Predictive value of post-percutaneous coronary intervention fractional flow reserve: a systematic review and meta-analysis
Authors: Andersen Birgitte Krogsgaard , Ding Daixin , Mogensen Lone Juul Hune , Tu Shengxian , Holm Niels Ramsing , Westra Jelmer , Wijns William
Published: August 2022

Aims

We aimed to investigate the relationship between post-percutaneous coronary intervention (PCI) fractional flow reserve (FFR) and clinical outcome using a systematic review with a study-level meta-analysis.

Methods and results

MEDLINE, Embase, and CENTRAL were systematically searched for articles with clinical follow-up reporting mean or median final post-PCI FFR. The main outcome was a composite of major adverse cardiac events (MACE) including all-cause death, myocardial infarction (MI), and target vessel revascularization (TVR). Meta-regression analyses were performed on mean post-PCI FFR values. A total of 62 studies with 12 340 patients and 12 923 stented vessels were included, with follow-ups ranging from 1 to 89 months. Post-PCI FFR was not continuously associated with the rate of 1-year MACE or 1-year TVR using meta-regression models accounting for heterogeneous follow-up lengths. For studies comparing high vs. low post-PCI FFR, low post-PCI FFR was associated with high risk ratio for MACE {1.97 [95% confidence interval (CI):1.45–2.67]}, all-cause death [1.59 (95% CI: 1.08–2.34)], MI [3.18 (95% CI: 1.84–5.50)], TVR [2.08 (95% CI: 1.63–2.65)] and angina status [2.50 (95% CI: 1.53–4.06)] using different optimal cut-off values spanning from 0.80 to 0.95.

Conclusion

We found no clear continuous association between post-PCI FFR and clinical outcomes in this systematic study-level meta-analysis. In a subset of studies investigating binary classification, high post-PCI FFR was associated with a better clinical outcome than low post-PCI FFR.

We investigated the relationship between post-percutaneous coronary intervention (PCI) fractional flow reserve (FFR) and rate of major adverse cardiac events (MACE), including all-cause death, myocardial infarction (MI), and target vessel revascularization (TVR), using a systematic review and study-level meta-analysis, pooling 12 340 patients from 62 studies. Mean post-PCI FFR was not continuously associated with a 1-year MACE rate accounting for heterogenous follow-up lengths. Still, the risk ratio favoured high post-PCI FFR for reduced MACE, all-cause death, MI, TVR, and better angina status using different cut-offs.
Identification and Parametric Estimation of Empirical Dynamic Marriage Matching Models
Authors: Chen Liang , Choo Eugene
Published: August 2022

Marriage matching markets typically involve heterogenous agents participating in a dynamic, non-stationary environment. These features pose a considerable modelling challenge. In this paper, we develop a new parametric model of dynamic marriage that allows for market non-stationarity using a system of transitionary equilibria. We propose a method to identify and parametrically estimate the model by representing the model equilibrium with a fixed-point mapping. We apply our model to investigate how China’s one-child policy has affected the marriage distribution through its effect on the population and sex ratios.
Incidental coronary calcium in cancer patients treated with anthracycline and/or trastuzumab
Authors: Hooks Matthew , Sandhu Gurmandeep , Maganti Tejaswini , Chen Ko-Hsuan Amy , Wang Michelle , Cullen Ryan , Velangi Pratik S , Gu Christina , Wiederin Jason , Connett John , Brown Roland , Blaes Anne , Shenoy Chetan , Nijjar Prabhjot S
Published: August 2022

Aims

Cancer patients are at increased risk of cardiovascular disease (CVD) after treatment with potentially cardiotoxic treatments. Many cancer patients undergo non-gated chest computed tomography (NCCT) for cancer staging prior to treatment. We aimed to assess whether coronary artery calcification on NCCT predicts CVD risk in cancer patients.

Methods and results

Six hundred and three patients (mean age: 61.3 years, 30.8% male) with either breast cancer, lymphoma, or sarcoma were identified retrospectively. Primary endpoint was a major adverse cardiac event (MACE) composite including non-fatal myocardial infarction, new heart failure (HF) diagnosis, HF hospitalization, and cardiac death, with Fine-Gray analysis for non-cardiac death as competing risk. Secondary endpoints included a coronary composite and a HF composite. Coronary artery calcification was present in 194 (32.2%) and clinically reported in 85 (43.8%) patients. At a median follow-up of 5.3 years, 256 (42.5%) patients died of non-cardiac causes. Coronary artery calcification presence or extent was not an independent predictor of MACE [sub-distribution hazards ratio (SHR) 1.28; 0.73–2.27]. Coronary artery calcification extent was a significant predictor of the coronary composite outcome (SHR per two-fold increase 1.14; 1.01–1.28), but not of the HF composite outcome (SHR per two-fold increase 1.04; 0.95–1.14).

Conclusion

Coronary artery calcification detected incidentally on NCCT scans in cancer patients is prevalent and often not reported. Coronary artery calcification presence or extent did not independently predict MACE. Coronary artery calcification extent was independently associated with increased risk of CAD events but not HF events.