bluuebunny/crossref_metadata_2025 huggingface dataset:
Parametric control of Meissner screening in light-driven superconductors
Authors: Homann Guido , Cosme Jayson G , Mathey Ludwig
Published: October 2022

We investigate the Meissner effect in a parametrically driven superconductor using a semiclassical U(1) lattice gauge theory. Specifically, we periodically drive the z-axis tunneling, which leads to an enhancement of the imaginary part of the z-axis conductivity at low frequencies if the driving frequency is blue-detuned from the plasma frequency. This has been proposed as a possible mechanism for light-enhanced interlayer transport in YBa2C3O7−δ
(YBCO). In contrast to this enhancement of the conductivity, we find that the screening of magnetic fields is less effective than in equilibrium for blue-detuned driving, while it displays a tendency to be enhanced for red-detuned driving.
Lattice Boltzmann method with effective correction of phonon properties for nano/microscale heat transfer
Authors: Huang Yufeng , Hou Chaofeng , Ge Wei
Published: October 2022

The significant self-heating effect severely restricts the performance and reliability of nano-electronic devices. Accordingly, it is very important to understand the process and mechanism of nano/microscale heat transfer for thermal management and thermal design of devices. In this work, we propose a new Lattice Boltzmann Method (LBM) scheme with effective correction of phonon mean free path (MFP) and relaxation time to study phonon heat transfer in silicon thin films and silicon medium with defects, where the correction factor is dependent on the lattice structure of LBM. The transformation analysis of phonon transfer mechanism at different scales shows that the size effect of cross-plane thermal conductivity is more remarkable than that of in-plane thermal conductivity. And the thermal conductivity of silicon medium with defects decreases exponentially as defect density increases. The proposed new LBM scheme can generate more accurate results than the traditional ones in the heat conduction simulations of different nano/microscale structures.
Analysis of Landau–Lifshitz and neo-Hookean models for static and dynamic acoustoelastic testing
Authors: Melnikov Andrey , Malcolm Alison E , Poduska Kristin M
Published: October 2022

A comparison of three different isotropic non-linear elastic models uncovers subtle but important differences in the acoustoelastic responses of a material slab that is subjected to dynamic deformations during a pump-probe experiment. The probe wave deformations are small and are superimposed on larger underlying deformations using three different models: Landau–Lifshitz (using its fourth-order extension), compressible neo-Hookean model (properly accounting for volumetric deformations), and an alternative neo-Hookean model (fully decoupled energies due to distortional isochoric and volumetric deformations). The analyses yield elasticity tensors and respective expressions for the propagation speeds of P-wave and S-wave probes for each model. Despite having many similarities, the different models give different predictions of which probe wave types will have speeds that are perturbed by different pump wave types. The analyses also show a conceptual inconsistency in the Landau–Lifshitz model, that a simple shear deformation induces a stress and a shear wave probe speed that depend on the second-order elastic constant λ, which controls resistance to volumetric changes and thus should not be present in the expressions for shear stress and shear wave probe speeds. Thus, even though the Landau–Lifshitz model is widely used, it may not always be the best option to model experimental data.
A study of anisotropic thermoelectric properties of bulk Germanium Sulfide in its Pnma phase: a combined first-principles and machine-learning approach
Authors: Rakshit Medha , Nath Subhadip , Chowdhury Suman , Mondal Rajkumar , Banerjee Dipali , Jana Debnarayan
Published: October 2022

This work reports a detailed and systematic theoretical study of the anisotropic thermoelectric properties of bulk Germanium Sulfide (GeS) in its orthorhombic Pnma phase. Density functional theory (DFT), employing the generalized gradient approximation (GGA), has been used to examine the structural and electronic band structure properties of bulk GeS. Electronic transport properties have been studied by solving semiclassical Boltzmann transport equations. A machine-learning approach has been used to estimate the temperature-dependent lattice part of thermal conductivity. The study reveals that GeS has a direct band gap of 1.20 eV. Lattice thermal conductivity is lowest along crystallographic a-direction, with a minimum of ∼0.98 Wm
−1
K
−1 at 700 K. We have obtained the maximum figure of merit (ZT) ∼ 0.73 at 700 K and the efficiency ∼7.86% in a working temperature range of 300 K–700 K for pristine GeS along crystallographic a-direction.
Leakage of gravitational waves into an extra dimension in the DGP model
Authors: Khlopunov M. , Gal'tsov D.V.
Published: October 2022

In the DGP model, the graviton is unstable, which leads to a modification of gravity at cosmological distances. In particular, this leads to the leakage of gravitational waves from the brane into an extra dimension at large distances from the source. However, the calculation of the gravitational wave leakage intensity is a non-trivial task due to the violation of the Huygens principle in the five-dimensional bulk of the DGP setup. The odd dimension of the bulk makes it difficult to extract the radiated part of the field. In this paper, we consider a simplified problem of scalar radiation from a point charge localized on a brane in the framework of the scalar field analog of the DGP model. In this model, the scalar field on the brane can be represented as a continuous spectrum of Kaluza-Klein massive modes. To extract the emitted part of such a field, we generalize the Rohrlich-Teitelboim approach to radiation to the case of a massive four-dimensional field, using its connections to massless fields in four and five dimensions. In the case of a charge moving along a circular trajectory, we obtain the dependence of the radiation energy flux through a 2-sphere localized on the brane on the sphere radius, which provides the intensity of leakage of scalar radiation from the brane. Consistent with the infrared transparency of the bulk, the leakage intensity is found to be higher for low frequency signals. We are also analyzing the possibility of detecting this leak by current and future gravitational-wave observatories.
Analyses and optimizing of bidirectional quantum teleportation using a five-qubit cluster state as quantum channel
Authors: Yuan Hao , Liu Xiang-Yuan , Pan Guo-Zhu , Kong Min , Zhang Gang
Published: October 2022

Using a five-qubit cluster state as quantum channel, a novel bidirectional quantum teleportation protocol has been proposed by Wang and Li (2022 Quantum Inf. Process.
21 44) recently in which there are two legitimate parties, Alice and Bob. Alice can teleport a two-qubit pure entangled state to Bob, simultaneously Bob can teleport a single-qubit state to Alice. In this paper, based on the same five-qubit cluster state as quantum resource, we put forward an optimized protocol. A comparison with Wang and Li’s protocol is made which reveals distinct advantages of the optimized protocol in reducing the classical resources and degrading the complexity of necessary quantum operations, as well as increasing the inherent efficiency. Additionally, some mistakes in Wang and Li’s protocol are pointed out and amended.
Statistical numerical investigation of translational-rotational ultrafast image-based dynamic light scattering to measure a bimodal Gaussian sample of cylindrical nanoparticles
Authors: Zhao A Y , Wang J J , Han Y P , Aihoon F , Yang H , Briard P
Published: October 2022

In a translational-rotational ultrafast image-based dynamic light scattering (TR-UIDLS) experiment, nanoparticles in Brownian motion in a solvent are illuminated by a focused Gaussian beam and scatter the light toward a camera. If both vertical-vertical and vertical-horizontal polarization geometries are recorded at the same time, using a polarization camera, a distribution of “equivalent cylindrical particles” is determined from the cross-correlation coefficients between the pairs of pictures recorded by the camera in both polarization geometries. The equivalent cylindrical particles are the monodisperse cylindrical particles that scatter the same light fluctuations as the polydisperse particles in the measurement volume. The distribution of equivalent cylindrical particles is not strictly the distribution of the particles in the sample, and our purpose is to measure characteristic information about the size and shape of the particles in the sample from the distribution of the equivalent cylindrical particles. With this purpose, we propose in the present paper a model of numerical simulation of the TR-UIDLS experiment for polydisperse arbitrary distributions of cylindrical particles. The TR-UIDLS has been simulated for the bimodal Gaussian distribution of gold cylindrical nanorods immersed in water. In view of these simulations, a strategy is discussed to retrieve characteristic information about the bimodal Gaussian distribution of cylindrical particles.
Composition and pharmacological analysis of loach mucus
Authors: Li Ning , Qian Hao , Zhuo Qinghua , Xu Jiyun , Yu Kaihuan , Zheng Rongquan , Jin Genqing
Published: October 2022

Hydrogel plays an important role in the composition of biological tissue. Muscle, cell membrane, blood vessel wall, hair and cartilage in human body can be regarded as hydrogel. The mucus on the surface of natural living organisms such as loach, andrias davidianus and earthworm is natural hydrogel. This kind of mucus with peculiar smell is produced by living organisms due to external stimulation of body surface stress response. It is a kind of self-protection. And this mucus has certain effects of antibacterial, antifatigue and enhancing immunity. The main component of mucus is collagen with shorter molecular structure and molecular weight is relatively small, and the content of collagen can reach about 40 ∼ 60 % in mucus. It has a certain bonding effect on skin surface damage, and plays the function of quickly closing wounds and killing bacteria. Hyaluronic acid (HA), active structure in oligosaccharide peptide and collagen peptide extracted from mucus, particularly type II collagen, play important roles in skin repair. This function of this natural hydrogel may open a new approach for the development of secondary functions of such organisms.
Design of Wearable Multifunctional Electroscope
Authors: Ma Di , Wang Ning
Published: October 2022

With the development of science and technology, the principle and technology of non-contact electroscope are relatively mature and widely used. Therefore, the development of an electroscope with real-time monitoring, lightweight, portable and rich functions is of great significance to the safety of operators. In this paper, comparison of different sensors is used to determine the design of the monopole antenna. Then designing each module circuit and PCB, doing the hardware production of electroscope, writing software and debugging the system are completed. In order to facilitate maintenance monitoring, electroscope has wireless communication function, which can upload data to the monitoring platform APP through Bluetooth. In summary, the designed electroscope can realize the functions of near power early warning, time display, heart rate measurement and mobile app monitoring, achieve the expected purpose and requirements, and provide active and effective power safety protection for maintenance personnel in high voltage environment.
Design of Winner-Takes-All Circuits in Competitive Neural Networks
Authors: Feng Ziwei , Yaoxuan Liu , Li Tong , Liu Zelong , Ding Huan , Cao Xinzhou
Published: October 2022

The Winner-Take-All circuit is an important part of the competition layer in the competitive neural network. Its main function is to compare the size of the output of the nodes after the weighted summation of all input vectors, and select the node with the largest output to output high power level, while other nodes output low level, that is, to find the node with the largest output. According to the characteristics of the Winner-Take-All circuit in the competitive neural network, the simulation of the Winner-Take-All circuit is carried out by the PSPICE simulation software. The physical test results show that, like the simulation diagram of the Winner-Take-All circuit, it conforms to the logic truth table, which further confirms the rationality and correctness of the Winner-Take-All circuit. Hardware realization of Winner-Take-All circuit as an important component of competitive layer in competitive neural networks has important research significance.
Modeling Laminated Al2O3/HfO2 RRAM Based on Oxygen Vacancy Conduction
Authors: Du Yongqian , Liu Fang , Zhang Xuyan , Zhang Siyu
Published: October 2022

A Al2O3/HfO2 RRAM electro-thermal coupled model was constructed by CMOSOL, which considered the effect of oxygen vacancy. The model includes ion migration, electrical conduction and Joule heating models, and the parameters involved are the same as those of the fabricated devices. The model has include the effect of temperature and oxygen vacancy distribution. In addition, this paper simulates the resistance characteristics of the Reset/Set process, and compares and analyzes the difference between the fracture position and the internal mechanism of the conductive filaments in the laminated structure. The work can help further understand the mechanism of laminated Al2O3/HfO2 RRAM.
Enhancing EHR Implementation with Process Mining
Authors: Asare Esther , Wang Lili , Fang Xianwen
Published: October 2022

Hospitals have increased the adoption of Hospital Information Systems to optimize processes for the efficient and effective delivery of services to customers (i.e., patients). However, there are still challenges in adopting information systems in healthcare, despite technological advancements and the enormous business benefits. These challenges have led to resistance of some healthcare providers to use these systems. Moreover, investigative and diagnostic measures are not exhaustively carried out to improve the processes of healthcare centers and the implemented information systems used in executing the processes. Fortunately, process mining techniques help optimize business processes, but they are primarily utilized post-implementation/post-go-live. This paper demonstrates the role process mining can play in adopting an EMR/EHR by improving the existing EHR Implementation Lifecycle by proposing an Enhanced Model. We suggest using process mining at suitable phases of the EHR Implementation lifecycle, not post-implementation/post-go-live only. Therefore, we propose an Enhanced EHR Implementation Lifecycle that supports process mining as part of a testing protocol adopted for EMRs/EHRs usability in conformance to the organization’s workflow in other implementation phases. An experiment is performed with event logs from an open-source EHR for the feasibility of the proposed Enhanced EHR/EMR implementation model.
Automatic Sample Labeling Method for Radar Target Recognition
Authors: Sun Jingming , Zhang Qiang , Yang Jingbei , Yang Yuhao
Published: October 2022

Rapid and accurate recognition of target types is one of the key problems that must be solved to improve radar detection and perception performance. However, the existing radar target recognition technology faces the problems of low efficiency and low quality of sample labeling in practical application. Aiming at the urgent need of automatic sample labeling in radar target recognition, this paper proposes an automatic sample labeling method based on the matching of auxiliary source information and radar track information, which can effectively improve the efficiency and quality of sample labeling in radar target recognition. The experimental results show that the proposed method can effectively label the wide and narrow band data samples required for radar target recognition, and has the advantages of automatic process and high labeling accuracy.
Research on Maritime Navigation Perception Requirements of Intelligent Ships
Authors: Wang Yong , Gao Zengyun , Li Chunxu , Ge Fan , Wei Changgeng , Xu Jiaqing
Published: October 2022

Aiming at the problem that in the research and development process of the intelligent ship perception system, the fuzzy understanding of the perception demand causes the perception equipment to be inconsistent with the ship’s autonomous collision avoidance needs, based on the application practice of the 1972 “International Maritime Collision Avoidance Regulations” and the good marine craftsmanship of the mariners Based on the comparison and experience summary method, the ship pilot’s perception of navigation obstacles is analyzed, and the requirements for intelligent ship navigation perception at sea are proposed from five aspects: vision, ARPA radar, AIS, human-computer interaction, and electronic chart, it can provide theoretical support for the research of intelligent ship sensing system.
DCCTN: Deep Complex Convolution Transformer Network for Far-field and Low SNR Speech Enhancement
Authors: Sun Chang , Qin Bo
Published: October 2022

Single-channel speech enhancement has made great progress with the development of deep learning. Recently, some researchers predict the real and imaginary parts of the output respectively by deep complex convolutional networks and achieve state-of-art performance. Based on this, in this paper, we design a new network structure, called Deep Complex Convolution Transformer Network (DCCTN), which is dedicated to solving the problem of single-channel speech enhancement under the conditions of far-field and extremely low signal-to-noise ratio (SNR). First, based on the Deep Complex Convolution Recurrent Network (DCCRN), a two-stage transformer masking module is introduced to replace the recurrent network structure and better focus on the long-term correlation of speech. Secondly, the deep complex transformer structure and gaussian weight matrix are introduced to make the model more suitable for far-field and very low SNR scenarios. In the experiment, we mixed real far-field clean speech and noise to make training and test data sets. The experimental results show that in the target scene, DCCTN proposed has significantly improved speech-enhancement performance, compared to most of the latest methods.
Dynamic Task Allocation Method for Heterogenous Multiagent System in Uncertain Scenarios of Agricultural Field Operation
Authors: Liang Yajie , Zhou Kun , Wu Caicong
Published: October 2022

This study focuses on the problem of dynamic task allocation for a heterogeneous multiagent system (MAS) in uncertain scenarios and its application in agricultural field operation. Previous studies lacked robustness or efficiency for uncertain environments especially in agricultural field, such as agent removal, agent inclusion, changes of agent capabilities, and task changes. We present herein a novel concept of the potential field of capability influence (PFCI), and based on which, we can estimate potential overloaded tasks. This provides an opportunity to improve the allocation of the remaining tasks. Then, we propose a heuristic-based clustering auction (HBCA) method by introducing PFCI into the auction mechanism to achieve an effective and efficient task allocation. The whole method consists of the three following phases based on the auction mechanism: 1) auctioneer preprocessing phase that adopts a capability priority strategy to select the preferable agent; 2) bidder preprocessing phase that introduces the PFCI to obtain a list of clustered tasks heuristically; and 3) adaptive auction phase that applies the auction mechanism to achieve an appropriate match between agents and tasks. Numerical simulations with different uncertain field operation scenarios validate the effectiveness of the proposed method. The results show that the proposed HBCA can dramatically reduce the total assignment cost and outperform state-of-the-art methods, especially in the case of obvious variances in agent capabilities.
Increased Central European forest mortality explained by higher harvest rates driven by enhanced productivity
Authors: Scheel Marieke , Lindeskog Mats , Smith Benjamin , Suvanto Susanne , Pugh Thomas A M
Published: October 2022

Increasing tree growth and mortality rates in Europe are still poorly understood and have been attributed to a variety of drivers. This study explored the role of climate drivers, management and age structure in driving changes in tree mortality rates in six Central European countries from 1985 to 2010, using the process-based vegetation model LPJ-GUESS. Simulations show a strong positive trend in canopy mortality rates in Central Europe, consistent with satellite observations. This trend was explained by an assumed increase in managed thinning in response to a modelled increase in forest productivity caused by climate change and rising atmospheric CO2 concentration. Simulated rates of canopy mortality were highly sensitive to the minimum tree size threshold applied for inclusion in the rate calculation, agreeing with satellite observations that are likely to only capture the loss of relatively large trees. The calculated trends in mortality rate also differed substantially depending on the metric used (i.e. carbon, stem or canopy mortality), highlighting the challenge of comparing tree mortality trends from different observation types. We conclude that changes in forest productivity and management in combination can profoundly affect regional-scale patterns of tree mortality. Our findings underscore the fact that increasing forest mortality can occur without reductions in forest growth when mediated by management responses to increasing productivity.
Sesame oil as an effective, environmentally friendly synergist for insecticidal compositions based on neonicotinoids, pyrethroids and organophosphorus compounds
Authors: Mukovoz P , Dankovtseva E
Published: October 2022

To prevent the resistance of insect pests to insecticides, various methods are used - the rotation of the drugs used, the joint application of drugs from different chemical groups, the use of the fumigation method of biologically active compounds, as well as the inclusion of synergistic substances in insecticidal compositions that enhance the biological activity of the main active substance. The use of synergistic substances can significantly increase the effectiveness of insecticides at a lower consumption rate of the drug. The aim of the work was to develop effective insecticidal pyrotechnic compositions, including environmentally friendly synergistic substances based on sesame oil. As a result, effective insecticidal compositions were developed based on neonicotinoids, pyrethroids, organophosphorus compounds and sesame oil, which provides a significant synergistic effect of active substances on insect pests of agricultural crops - greenhouse whitefly (Trialeurodes vaporariorum). It was shown that during the treatment by spraying, the composition containing 24% of sesame oil, as well as 86% of neonicotinoids, pyrethroids, and organophosphorus compounds had the greatest insecticidal effect (27% death of insects). When carrying out the treatment by fumigation, the compositions containing 23–24% of sesame oil, as well as 87–86% of these insecticides, had the greatest insecticidal effect (more than 90% of insect death). It is shown that the developed compositions can be used both by spraying agricultural plants and by fumigation, by burning a pyrotechnic composition mixed with a composite base. Fumigation has been found to be the most effective method of delivering insecticidal compositions to pests of agricultural plants.
Comparative spectral analysis of Gatchina water sources and melted snow as their possible contaminator
Authors: Molodkina L M , Sukhareva A V
Published: October 2022

Using the methods of spectrophotometry and spectrofluorimetry, samples of five Gatchina water sources and samples of melted snow taken in a residential area, the city center and near the central highway were studied in the paper. Both methods have demonstrated their informativeness in the analysis of differences in pollution of different water sources. Contamination of samples of melted snow with oil products is clearly shown in the analysis of the registration and excitation fluorescence spectra. To detect pollution of water sources by oil products contained in melted snow, it is proposed to determine the ratios of fluorescence intensity in the spectra of registration and excitation at certain wavelengths.
Energy-efficient process for low-temperature recycling of oil sludge waste
Authors: Abdeev E R , Meshalkin V P , Saitov R I , Abdeev R G , Fatykhov M A
Published: October 2022

The existing methods of processing of hydrocarbon wastes have significant drawbacks. The installation and functional models of petrochemical apparatuses for studying the microwave effect on the water-in-oil emulsion of oil sludge waste were developed in this article. An empirical dependence of the sedimentation rate of water globules in oil products under microwave radiation and a numerical model were obtained. The method of intensifying the stratification of oil products, which allows to save on other ways of impact and to solve environmental problems was substantiated
Measurement of specular surfaces using electrically tunable lens in digital holography
Authors: Barak Neelam , Kumari Vineeta , Sheoran Gyanendra
Published: October 2022

In the field of industrial metrology, the 3D nondestructive imaging of reflective metallic surfaces is a delicate task. In this work, we propose a novel application of the electrically tunable lens (ETL) in digital holography for imaging specularly reflecting objects. The precise surface profile of the microscopic step height at different axial depths is obtained by tuning the liquid lens at different currents. Initially, the ETL’s focal length is set by tuning its control current to image the specular reflection observed from the surface of the reflecting sample. The current of the ETL is tuned accordingly as the sample is moved to different z-positions. In order to demonstrate the efficacy of the proposed setup, the object is kept at multiple axial distances within the depth of field of the ETL. The step height measurements are carried out and a measurement uncertainty of 0.083 µm is calculated for step height measurements at different axial positions ranging from 2 cm–21 cm. The axial range of the setup is validated by keeping two specularly reflecting samples in the field of view of the ETL. The experimental results demonstrate the ETL’s efficiency in a digital holographic system for accurately imaging specularly reflecting objects present at multiple axial depths. The setup is useful for precise step height measurements and for obtaining surface profiles of microstructures.
Nanoscale insights into the structure of solution-processed graphene by x-ray scattering
Authors: Yan Zhengyu , Guimarey María J G , Parvez Khaled , Dun Chaochao , Read Oliver , Forrest Thomas , Urban Jeffrey J , Abdelkader Amor , Casiraghi Cinzia , Mirihanage Wajira
Published: October 2022

Chemical exfoliation is an attractive approach for the synthesis of graphene due to its low cost and simplicity. However, challenges still remain in the characterization of solution-processed graphene, in particular with atomic resolution. Through this work we demonstrate the x-ray pair distribution function as a novel approach to study solution-processed graphene or other 2D materials with atomic resolution, directly in solution, produced by liquid-phase and electrochemical exfoliations. The results show the disappearance of long-range atomic correlations, in both cases, confirming the production of single and few-layer graphene. In addition, a considerable ring distortion has been observed as compared to graphite, irrespective of the solvent used: the normal surface angle to the sheet of the powder sample should be less than 6°, compatible with ripples formation observed in suspended graphene. We attribute this effect to the interaction of solvent molecules with the graphene nanosheets.
Hypoxia adapted relative biological effectiveness models for proton therapy: a simulation study
Authors: Garrido-Hernandez Guillermo , Henjum Helge , Høiskar Marte Kåstad , Dahle Tordis Johnsen , Redalen Kathrine Røe , Ytre-Hauge Kristian Smeland
Published: October 2022

In proton therapy, a constant relative biological effectiveness (RBE) factor of 1.1 is applied although the RBE has been shown to depend on factors including the Linear Energy Transfer (LET). The biological effectiveness of radiotherapy has also been shown to depend on the level of oxygenation, quantified by the oxygen enhancement ratio (OER). To estimate the biological effectiveness across different levels of oxygenation the RBE-OER-weighted dose (ROWD) can be used. To investigate the consistency between different approaches to estimate ROWD, we implemented and compared OER models in a Monte Carlo (MC) simulation tool. Five OER models were explored: Wenzl and Wilkens 2011 (WEN), Tinganelli et al 2015 (TIN), Strigari et al 2018 (STR), Dahle et al 2020 (DAH) and Mein et al 2021 (MEI). OER calculations were combined with a proton RBE model and the microdosimetric kinetic model for ROWD calculations. ROWD and OER were studied for a water phantom scenario and a head and neck cancer case using hypoxia PET data for the OER calculation. The OER and ROWD estimates from the WEN, MEI and DAH showed good agreement while STR and TIN gave higher OER values and lower ROWD. The WEN, STR and DAH showed some degree of OER-LET dependency while this was negligible for the MEI and TIN models. The ROWD for all implemented models is reduced in hypoxic regions with an OER of 1.0–2.1 in the target volume. While some variations between the models were observed, all models display a large difference in the estimated dose from hypoxic and normoxic regions. This shows the potential to increase the dose or LET in hypoxic regions or reduce the dose to normoxic regions which again could lead to normal tissue sparing. With reliable hypoxia imaging, RBE-OER weighting could become a useful tool for proton therapy plan optimization.
A meta-analysis of the relationship between climate change experience and climate change perception
Authors: Xia Ziqian , Ye Jinquan , Zhou Yongan , Howe Peter D , Xu Ming , Tan Xianchun , Tian Xi , Zhang Chao
Published: October 2022

Will climate change experience shape people’s climate change perception? To examine the evidence, we performed a pre-registered meta-analysis using data from 302 studies, covering 351,378 observations. Our results find that climate change experience only has a weak positive correlation with climate change awareness in general (r = 0.098, 95% CI 0.0614, 0.1348), and the effect sizes vary considerably across different climate events. General hazard and temperature anomalies experiences have significant correlations, but other events exhibit no or neglectable effects. The moderator analysis showed that self-reported studies result in higher correlations, whereas studies based on victims’ actual experiences report lower effect sizes. Our study suggests that people’s climate change experiences may not be effective in shaping their awareness of climate change, which is likely due to people’s attribution style and adaptability. The importance of proactive education thus is further emphasized to raise the awareness of climate change.
Beyond classification: directly training spiking neural networks for semantic segmentation
Authors: Kim Youngeun , Chough Joshua , Panda Priyadarshini
Published: October 2022

Spiking neural networks (SNNs) have recently emerged as the low-power alternative to artificial neural networks (ANNs) because of their sparse, asynchronous, and binary event-driven processing. Due to their energy efficiency, SNNs have a high possibility of being deployed for real-world, resource-constrained systems such as autonomous vehicles and drones. However, owing to their non-differentiable and complex neuronal dynamics, most previous SNN optimization methods have been limited to image recognition. In this paper, we explore the SNN applications beyond classification and present semantic segmentation networks configured with spiking neurons. Specifically, we first investigate two representative SNN optimization techniques for recognition tasks (i.e., ANN-SNN conversion and surrogate gradient learning) on semantic segmentation datasets. We observe that, when converted from ANNs, SNNs suffer from high latency and low performance due to the spatial variance of features. Therefore, we directly train networks with surrogate gradient learning, resulting in lower latency and higher performance than ANN-SNN conversion. Moreover, we redesign two fundamental ANN segmentation architectures (i.e., Fully Convolutional Networks and DeepLab) for the SNN domain. We conduct experiments on three semantic segmentation benchmarks including PASCAL VOC2012 dataset, DDD17 event-based dataset, and synthetic segmentation dataset combined CIFAR10 and MNIST datasets. In addition to showing the feasibility of SNNs for semantic segmentation, we show that SNNs can be more robust and energy-efficient compared to their ANN counterparts in this domain.
Nationwide assessment of ambient monthly fine particulate matter (PM2.5) and the associations with total, cardiovascular and respiratory mortality in the United States
Authors: Rau Austin , Abadi Azar , Fiecas Mark B , Gwon Yeongjin , Bell Jesse E , Berman Jesse D
Published: October 2022

High air pollution events spanning multiple months and caused by environmental perturbations such as droughts and wildfires are increasing in frequency, intensity and duration due to climate change. While both daily and annual exposure to fine particulate matter (PM2.5) have regulatory standards in the United States, mid-scale exposure at the monthly interval remains unregulated and the public health impacts of mid-duration ambient air pollution exposure are poorly understood. These present a new public health challenge in mitigating harmful effects of persistent ambient air pollution on community health. We executed an ecological study of the associations between monthly mean PM2.5 exposure with total, cardiovascular and respiratory mortality counts, stratified by age, sex and race, in 698 counties in the conterminous United States from 1999 to 2018. A two-stage model was used to estimate the risk and number of deaths associated with this exposure timescale reported as incidence rate ratios (IRRs) and absolute risk differences per million persons (ARDs). Increased mortality of all types was positively associated with a 10 μg m−3 monthly change in PM2.5 exposure (total mortality IRR: 1.011, 95% confidence interval (CI): (1.009, 1.013), ARD: 8.558, 95% CI: (6.869, 10.247); cardiovascular mortality IRR: 1.014, 95% CI: (1.011, 1.018), ARD: 3.716, 95% CI: (2.924, 4.509); respiratory mortality IRR: 1.016, 95% CI: (1.011, 1.023), ARD: 1.676, 95% CI: (1.261, 2.091)). Our results suggest elderly, non-black minorities and males to be the most impacted subgroups along with metropolitan and highly socially vulnerable communities. Heterogeneities in the magnitude and direction of association were also detected across climate regions of the United States. These results elucidate potential effects of monthly PM2.5 on mortality and demonstrate a need for future health policies for this currently unregulated interval of ambient air pollution exposure.
Cyclic multiplicity of a direct sum of forward and backward shifts
Authors: Gu Caixing
Published: October 2022

Let

E
E

and

F
F

be two complex Hilbert spaces. Let

S

E

S_{E}

and

S

F

S_{F}

be the shift operators on vector-valued Hardy space

H

E

2

H_{E}^{2}

and

H

F

2

H_{F}^{2}

, respectively. We show that the cyclic multiplicity of

S

E

⊕

S

F

∗

S_{E}\oplus S_{F} ^{\ast }

equals

1
+
dim
⁡
E

1+\dim E

. This result is classical when

dim
⁡
E
=
dim
⁡
F
=
1

\dim E=\dim F=1

(see J. A. Deddens [On

A
⊕

A
∗

A \oplus A^\ast

, 1972]; Paul Richard Halmos [A Hilbert space problem book, Springer-Verlag, New York-Berlin, 1982]; Domingo A. Herrero and Warren R. Wogen [Rocky Mountain J. Math. 20 (1990), pp. 445–466]). Our approach is inspired by the elegant and short proof of this classical result attributed to Nikolskii, Peller and Vasunin in Halmos’s book [A Hilbert space problem book, Springer-Verlag, New York-Berlin, 1982]. By using the invariant subspace theorems for

S

E

⊕

S

F

∗

S_{E}\oplus S_{F}^{\ast }

(see M. C. Câmara and W. T. Ross [Canad. Math. Bull. 64 (2021), pp. 98–111]; Caixing Gu and Shuaibing Luo [J. Funct. Anal. 282 (2022), 31 pp.]; Dan Timotin [Concr. Oper. 7 (2020), pp. 116–123]), we characterize non-cyclic subspaces of

S

E

⊕

S

F

∗

S_{E}\oplus S_{F}^{\ast }

when

dim
⁡
E
>
∞

\dim E>\infty

and

dim
⁡
F
=
1

\dim F=1

.
Associations of Air Pollution and Genetic Risk With Incident Dementia: A Prospective Cohort Study
Authors: Zhang Zilong , Chen Lan , Wang Xiaojie , Wang Chongjian , Yang Yin , Li Haitao , Cai Miao , Lin Hualiang
Published: October 2022

Evidence on the association between air pollution and dementia is accumulating but still inconclusive, and the potential effect modification by genetics is unclear. We investigated the joint effects of air pollution exposure and genetic risk on incident dementia in a prospective cohort study, the UK Biobank study. Land use regression models were used to estimate exposure to ambient particulate matter (PM) in 3 fraction sizes (PM with diameter < 2.5 μm (PM2.5), coarse particles (PM with diameter 2.5–10 μm (PMc)), and PM with diameter < 10 μm (PM10)), PM2.5 absorbance, nitrogen dioxide levels, and nitrogen oxide levels at each individual’s baseline residence. A polygenic risk score was calculated as a quantitative measure of genetic dementia risk. Incident cases of dementia were ascertained through linkage to health administrative data sets. Among the 227,840 participants included in the analysis, 3,774 incident dementia cases (including 1,238 cases of Alzheimer disease and 563 cases of vascular dementia) were identified. After adjustment for a variety of covariates, including genetic factors, positive associations were found between exposure to air pollution—particularly PM10, PM2.5 absorbance, and nitrogen dioxide—and incident all-cause dementia and Alzheimer disease but not vascular dementia. No significant interaction between air pollution and genetics was found, either on the multiplicative scale or on the additive scale. Exposure to air pollution was associated with a higher risk of developing dementia regardless of genetic risk.
A rapid bacterial pathogen and antimicrobial resistance diagnosis workflow using Oxford nanopore adaptive sequencing method
Authors: Cheng Hang , Sun Yuhong , Yang Qing , Deng Minggui , Yu Zhijian , Zhu Gang , Qu Jiuxin , Liu Lei , Yang Liang , Xia Yu
Published: October 2022

Metagenomic sequencing analysis (mNGS) has been implemented as an alternative approach for pathogen diagnosis in recent years, which is independent of cultivation and is able to identify all potential antibiotic resistance genes (ARGs). However, current mNGS methods have to deal with low amounts of prokaryotic deoxyribonucleic acid (DNA) and high amounts of host DNA in clinical samples, which significantly decrease the overall microbial detection resolution. The recently released nanopore adaptive sampling (NAS) technology facilitates immediate mapping of individual nucleotides to a given reference as each molecule is sequenced. User-defined thresholds allow for the retention or rejection of specific molecules, informed by the real-time reference mapping results, as they are physically passing through a given sequencing nanopore. We developed a metagenomics workflow for ultra-sensitive diagnosis of bacterial pathogens and ARGs from clinical samples, which is based on the efficient selective ‘human host depletion’ NAS sequencing, real-time species identification and species-specific resistance gene prediction. Our method increased the microbial sequence yield at least 8-fold in all 21 sequenced clinical Bronchoalveolar Lavage Fluid (BALF) samples (4.5 h from sample to result) and accurately detected the ARGs at species level. The species-level positive percent agreement between metagenomic sequencing and laboratory culturing was 100% (16/16) and negative percent agreement was 100% (5/5) in our approach. Further work is required for a more robust validation of our approach with large sample size to allow its application to other infection types.
Criminal Court Sentencing: The Case for Specialist ‘Young Adult’ Courts
Authors: Ward Jennifer , Spence Ruth
Published: October 2022

Treating young adults (18–25 year olds) as a distinct group within the criminal justice system is receiving growing support. This article asks three specific questions. Should specialist young adult courts be introduced so that young age and developing maturity are considered with more consistency across court sentencing; should social background factors be taken into account when appraising culpability and have the 2019 ‘sentencing guidelines’ that give judicial direction for sentence mitigation gone far enough? The article argues significant gains in sentencing policy have been made, but a specialist young adult court model would ensure a dedicated response to this age group and would foster a shared courts working culture that pursues the common goals of rehabilitation and social pedagogic interventions.
Assessment Of Left and Right Ventricular Functions In Overweight and Obese Females by Different Echo-Doppler Modalities
Authors: Mohamed Layla A , Agiba Nadia A , Bassuony Samar M
Published: October 2022

Aim of work

Assessment of left and right ventricular functions in overweight and obese females using different echo-Doppler modalities.

Methods

This study included 32 obese females (group I), 26 overweight females (group II) -both of them have no chronic illnesses- in addition to 25 healthy females (group III) as a control group. All of them had hsCRP level measured. The following parameters were measured using 2D echocardiography: LA, Ao, LA/Ao ratio, LV measures included LV dimensions, 2D LVEF, 2D LV global longitudinal strain (LVGLS), average LV Sm, Em, Am, LV E/Em ratio, LV E, A and LV E/A ratio. RV measures included LV dimensions, RV FAC, RV Tei index, TAPSE, RV Sm, Em, Am, Em/Am ratio, RV E, A, E/A ratio and PASP.

Results

hsCRP, LA, Ao, LV dimensions, Average LV Am, E/Em, RVD1, RV Tei and PASP were significantly higher in group I compared to group III, but group I had significantly lower LV E/A, LV Sm, Em, LVGLS, RV E/A, Em/Am and RVGLS compared to group III. Group II had significantly higher hsCRP, Ao and RV Tei and significantly lower LV E/A ratio and LV Em compared to group III. On the other hand, group, I had significantly lower average Sm, LVGLS and RVGLS than group II but no significant difference detected between two groups as regard LV and RV diastolic function. Pulse, BMI, BSA, waist circumference, waist to hip ratio, hsCRP were negatively correlated with LVGLS and RVGLS. Cut-off values for BMI showed good sensitivity and specificity to predict impaired LVGLS and RVGLS. Cut-off point 31.9 kg/m2 for impaired LVGLS with sensitivity 80%, specificity 76.81% and p value <0.001, cut-off point >30.73kg/m2 for impaired RVGLS with sensitivity 80%, specificity 69.57% and p value 0.001.

Waist circumference was the most sensitive predictor for impaired LVGLS and hsCRP for impaired RVGLS.

Conclusion

Isolated obesity and overweight are independent predisposing factors for impaired LV and RV systolic and diastolic dysfunctions. TDI and 2D STE are good echo-Doppler modalities to detect subclinical effects on LV and RV functions.

Additional Content

An author video to accompany this abstract is available on https://academic.oup.com/eurheartjsupp. Please click on the arrow next to ‘More Content’ and then click on ‘Author videos’.
Impact of Cardiac Resynchronization Therapy (CRT) on the Severity of Mitral Regurgitation in Dilated Cardiomyopathy Patients
Authors: Magdy Gehan , Zaki Amr , Abdelwahab Ramzeya Mohamed , Sanhoury Mohamed
Published: October 2022

Aim

Functional Mitral regurge in advanced Heart failure dilated cardiomyopathy patients is a strong predictor to mortality, this arouses studying the impact of Cardiac resynchronization therapy on functional MR in DCM.

Methods and results

This is a prospective observational study of Twenty-five patients with advanced heart failure DCM with sinus rhythm LBBB wide QRS≥ 130 ms with at least moderate MR, subjected to CRT implantation at Alexandria main university Hospital and followed up by Echocardiography after CRT by 1 week and 10 weeks and comparing between improved MR (Group 1) and stable MR group patients (Group 2). FMR improvement was observed in 15 patients (60%) ‘Group 1’ (p value <0.001) vs 10 patients (40%) show stable MR ‘Group 2’. Evidence of early response to CRT was observered in 9 patients (36%). MR improvement among responders to CRT was observed in 7 patients (77.8%) and was higher among early echocardiographic responders (48%) than among early clinical responders (40%). MR improvement was significantly associated with percent of reduction in QRS width in surface ECG. (P value: 0.026).

Conclusions

CRT improves the degree of severity of functional MR among DCM patients. Improvement of MR severity is significantly associated with baseline QRS width and percent of reduction in QRS width.

Additional Content

An author video to accompany this abstract is available on https://academic.oup.com/eurheartjsupp. Please click on the arrow next to ‘More Content’ and then click on ‘Author videos’.