bluuebunny/crossref_metadata_2025_split huggingface dataset:
Memory-induced oscillations of a driven particle in a dissipative correlated medium
Authors: Venturelli Davide , Gambassi Andrea 
Published: August 2023

Abstract
The overdamped dynamics of a particle is in general affected by its interaction with the surrounding medium, especially out of equilibrium, and when the latter develops spatial and temporal correlations. Here we consider the case in which the medium is modeled by a scalar Gaussian field with relaxational dynamics, and the particle is dragged at constant velocity through the medium by a moving harmonic trap. This mimics the setting of an active microrheology experiment conducted in a near-critical medium. When the particle is displaced from its average position in the nonequilibrium steady state, its subsequent relaxation is shown to feature damped oscillations. This is similar to what has been recently predicted and observed in viscoelastic fluids, but differs from what happens in the absence of driving or for an overdamped Markovian dynamics, in which cases oscillations cannot occur. We characterize these oscillating modes in terms of the parameters of the underlying mesoscopic model for the particle and the medium, confirming our analytical predictions via numerical simulations.
Piecewise time-delay tri-stable stochastic resonance system and its application in bearing fault diagnosis
Authors: He Lifang , Chen Yezi , Zhang Huaan 
Published: August 2023

Abstract
Current studies of time-delay based systems are compared to classical tri-stable stochastic resonance (CTSR) system and do not reflect the effect of adding a delay term on unsaturated systems. In this paper, a piecewise delayed tri-stable stochastic resonance (PTTSR) system is proposed. Firstly, the equivalent Langevin for PTTSR system is derived and compared with the output of CTSR and piecewise tri-stable stochastic resonance (PTSR) systems, where the addition of the time-delay term can further improve the output amplitude. Secondly, mean first pass time (MFPT) and output signal-to-noise ratio (SNR) are derived, and the effects of different parameters on MFPT and SNR are investigated. increasing the feedback intensity and time-delay length improved the output SNR. Then, the input period signal is then numerically simulated using the signal-to-noise ratio gain (SNRG) as a measurement, which increases by 2.75 dB for PTTSR system compared to PTSR system. Finally, the three systems are used for bearing fault detection and the system parameters are optimized by genetic algorithm. The results showed that the output amplitude of PTTSR system is more than 12 times that of PTSR system and the SNRG increased by more than 2 dB. This demonstrates the superior performance of PTTSR system in detecting weak signals and provides good feasibility in engineering applications.
Analytical model of z-piezoelectric energy harvester for power generation from human physical activities
Authors: Sirigireddy Pravallika , Eladi Paul Braineard 
Published: August 2023

Abstract
Human physical activities, viz., walking, jogging, jumping, etc on piezoelectric energy harvesters (PEH) have a great potential for the generation of free and clean energy. In the present work, an analytical model is developed to study the performance of a z-PEH, and the results were validated with numerical and experimental results. The distinctive features of the z-PEH are (a) it can be installed in a very small pavement/road surface area, (b) it results in very less damage to the road during installation, and (c) the repair and maintenance works can be carried out relatively easily. The power generation of the harvester can be enormously increased by increasing the number of unimorphs in the vertical (z) direction without increasing in the surface (x-y) directions, hence termed z-PEH. The harvester studied has four unimorphs. Each unimorph has a PZT-5A plate and an Aluminum substrate. The analytical and numerical studies resulted in a harvester with optimum dimensions for the PZT plate and Aluminum substrate of 20 × 20 × 0.4 mm3 and 65.1 × 20 × 1 mm3 respectively. Experiments were carried out on the optimum structure. The z-PEH, for an input deflection of 1 mm generated a maximum power of 0.84 mW, 0.88 mW and 0.80 mW from the proposed analytical model, numerical work and experiments respectively. The percentage of error between analytical and numerical results is 4.55% and between analytical and experimental results is 4.76%. An average human can generate a force of 490 N while walking, thereby allowing the use of 88 unimorphs in the z-PEH. From the analytical model, the resulted DC power of this harvester is 18.39 mW and the power density is 10.09 W m−3.
Hidden dynamics of memristor-coupled neurons with multi-stability and multi-transient hyperchaotic behavior
Authors: Ma Tao , Mou Jun , Al-Barakati Abdullah A , Jahanshahi Hadi , Miao Miao 
Published: August 2023

AbstractThe coupling of memristors has been extensively studied in continuous neural models. However, little attention has been given to this aspect in discrete neural models. This paper introduces a Discrete Memristor-Coupled Rulkov Neuron (DMCRN) map, utilizing discrete memristors to estimate synaptic functionality. The proposed model is subjected to theoretical analysis, revealing hidden behaviors within the map. Through numerical methods, the rich and complex dynamical behaviors of the DMCRN map are studied, including hyperchaos, hidden attractors, multi-stability and multi-transient, as well as the firing patterns. Additionally, a simple pseudo-random sequence generator (PRNG) is designed based on the generated hyperchaotic sequences, providing a reference for further applications of DMCRN map. In addition, a digital experiment is implemented on a DSP platform, realizing the DMCRN map and obtaining hyperchaos. Both experimental and numerical results demonstrate that the coupling of discrete memristors allows for the estimation of synaptic connections in neurons, resulting in a more complex and interesting discrete neuron model.
Improvement of plastic property of Ti/Al nanowires by designing the core–shell structures
Authors: Gao Tinghong , Ding Yi , Liu Yutao , Bian Zhetian , Chen Qian , Xiao Qingquan , Xie Quan 
Published: August 2023

Abstract
Ti alloy has the disadvantages of low elastic modulus, high yield ratio, and low plasticity, therefore, improving its plasticity is very important to promote their use. In this study, the tensile behavior of Ti/Al core–shell nanowires (NWs) in the z-axis direction of single-crystal Ti with [0001] grain-oriented HCP structure and single-crystal Al with [001] grain-oriented FCC structure was investigated using molecular dynamic (MD) simulations to explore the mechanism of enhanced ductility in Ti alloy. The results indicate that the shell thickness may significantly affect the mechanical behaviors of the NWs. For the mechanical properties of core–shell NWs, Young’s modulus, ultimate tensile strength (UTS), Specific modulus, Specific strength, flow stress, and fracture strain showed sensitivity to shell thickness. Compared with core–shell NWs, single crystal Ti NW has greater strength and higher Young’s modulus, Specific strength and UTS. By contrast, core–shell NWs have better Specific modulus and plastic properties, their flow stress and fracture strain are higher than those of single crystal Ti NW. For the single crystal Ti NW, the main plastic deformation mechanisms are shear band nucleation and recrystallization. For Ti/Al core–shell NWs with shell thicknesses of 1and 2 nm, the nucleation of the twin variants replaces the dominant position of the shear bands. As the twin boundaries (TBs) expand, the dislocation slip is activated, and grain reorientation occurs, inducing the superior plastic properties of NWs. As the shell thickness increases to 3–5 nm, the interaction between the twin variants and shear bands reduces the expansion rate of the TBs, resulting in increased flow stress and fracture strain of the NWs. This study can provide theoretical guidance for the experimental study and preparation of core–shell NWs.
Searching for relativistic axions in the sky
Authors: Kar Arpan , Kumar Tanmoy , Roy Sourov , Zupan Jure 
Published: August 2023

Abstract
Relativistic axions produced in decays of
𝒪(10-7–10-2 eV) dark matter (DM) partially convert to photons after
traversing the galactic magnetic field, giving rise to a signal observable by the Square Kilometer Array (SKA) radio telescope.
We show that for axions lighter than a few × 10-13 eV a 100 h SKA observation of the local dwarf galaxy Seg I would probe parameter space not constrained
by stellar cooling and cosmological observations, with sensitivity several orders of magnitude
better than the planned dedicated axion dark matter search experiments.
We quantify the uncertainties in the SKA sensitivity projections due to two effects that enhance the radio flux:
the presence of turbulent magnetic fields inside the galaxy, and the Bose enhancement of the DM decays to axions, where the latter, in particular, warrants further study.
Optical fiber temperature sensor based on beat frequency and Vernier effect of fiber ring resonator composite cavity
Authors: Wang Xu , Li Kecheng , Wu Xiaoyang , Li Bing , Wang Fang , Yu Kun 
Published: August 2023

Abstract
A fiber temperature sensing scheme based on beat frequency and Vernier effect of fiber ring resonator (FRR) with composite cavity is proposed and experimentally demonstrated. The optical FRR as a sensor is put into the linear cavity fiber laser, and Vernier effect is generated when the resonance spectrum of the optical FRR and the longitudinal mode of the laser are superimposed. The beat frequency envelope spectrum corresponding to the longitudinal mode Vernier spectrum is used to realize fiber ring sensing in electrical domain, and the sensing information is obtained by tracing the envelope of beat frequency signal, which has the advantages of stable system, simple structure, low cost and high sensitivity.
On nonlinear scattering of drift wave by toroidal Alfvén eigenmode in tokamak plasmas
Authors: Chen Liu , Qiu Zhiyong , Zonca Fulvio 
Published: August 2023

Abstract
Using electron drift wave (eDW) as a paradigm model, we have investigated analytically direct wave–wave interactions between a test DW and ambient toroidal Alfvén eigenmodes (TAEs) in toroidal plasmas, and their effects on the stability of the eDW. The nonlinear effects enter via scatterings to short-wavelength electron Landau damped kinetic Alfvén waves (KAWs). Specifically, it is found that scatterings to upper-sideband KAW lead to stimulated absorption of eDW. Scatterings to the lower-sideband KAW, on the contrary, lead to its spontaneous emission. As a consequence, for typical parameters and fluctuation intensity, nonlinear scatterings by TAEs have negligible net effects on the eDW stability; in contrast to the ‘reverse’ process investigated in Chen et al (2022 Nucl. Fusion
62 094001), where it is shown that nonlinear scattering by ambient eDWs may lead to significant damping of TAE.
Leveraging large language models to monitor climate technology innovation
Authors: Toetzke Malte , Probst Benedict , Feuerriegel Stefan 
Published: August 2023

AbstractTo achieve net-zero emissions, public policy needs to foster rapid innovation of climate technologies. However, there is a scarcity of comprehensive and up-to-date evidence to guide policymaking by monitoring climate innovation systems. This is notable, especially at the center of the innovation process, where nascent inventions transition into profitable and scalable market solutions. Here, we discuss the potential of large language models (LLMs) to monitor climate technology innovation. By analyzing large pools of unstructured text data sources, such as company reports and social media, LLMs can automate information retrieval processes and thereby improve existing monitoring in terms of cost-effectiveness, timeliness, and comprehensiveness. In this perspective, we show how LLMs can play a crucial role in informing innovation policy for the energy transition by highlighting promising use cases and prevailing challenges for research and policy.
3D printing of photochromic and thermochromic shape memory polymers for multi-functional applications
Authors: Ge Nengpeng , Shan Wubin , Liang Lei , Deng Yuancheng , Wu Linmei 
Published: August 2023

Abstract
The field of 3D printing is growing rapidly and offers a wide range of potential applications, particularly with the use of Shape Memory Polymers (SMPs). However, current studies on SMP-based 3D printing have mainly focused on structural design and deformation behavior. To enhance the practicality of 3D printed structures, the ability to change color is highly desirable, especially for applications such as anti-counterfeiting, encryption, and bioinspired camouflage. This paper presents the fabrication of a UV-curable PUA-based Shape Memory Polymer (SMP) system with thermochromic and photochromic capabilities. The system is acrylate-based, making it highly UV-curable and compatible with high-resolution 3D printing techniques. Thermo/photochromic effects are achieved by adding thermochromic microcapsules to the system, resulting in printed structures that can change color upon heating or UV) exposure. The printed parts with multi-color hidden information, such as QR codes and digital numbers, were successfully demonstrated through the printing of various anti-counterfeiting patterns.And the expriment results show the exceptional multi-functional performance including shape recovery and thermo/photochromic. The development of this UV-curable PUA-based SMP system represents a significant advancement in the application of SMP-based 3D printing for anti-counterfeiting and secure data recording.
Spatiotemporal denoising of low-dose cardiac CT image sequences using RecycleGAN
Authors: Zhou Shiwei , Yang Jinyu , Konduri Krishnateja , Huang Junzhou , Yu Lifeng , Jin Mingwu 
Published: August 2023

Abstract
Electrocardiogram (ECG)-gated multi-phase computed tomography angiography (MP-CTA) is frequently used for diagnosis of coronary artery disease. Radiation dose may become a potential concern as the scan needs to cover a wide range of cardiac phases during a heart cycle. A common method to reduce radiation is to limit the full-dose acquisition to a predefined range of phases while reducing the radiation dose for the rest. Our goal in this study is to develop a spatiotemporal deep learning method to enhance the quality of low-dose CTA images at phases acquired at reduced radiation dose. Recently, we demonstrated that a deep learning method, Cycle-Consistent generative adversarial networks (CycleGAN), could effectively denoise low-dose CT images through spatial image translation without labeled image pairs in both low-dose and full-dose image domains. As CycleGAN does not utilize the temporal information in its denoising mechanism, we propose to use RecycleGAN, which could translate a series of images ordered in time from the low-dose domain to the full-dose domain through an additional recurrent network. To evaluate RecycleGAN, we use the XCAT phantom program, a highly realistic simulation tool based on real patient data, to generate MP-CTA image sequences for 18 patients (14 for training, 2 for validation and 2 for test). Our simulation results show that RecycleGAN can achieve better denoising performance than CycleGAN based on both visual inspection and quantitative metrics. We further demonstrate the superior denoising performance of RecycleGAN using clinical MP-CTA images from 50 patients.
Minmers are a generalization of minimizers that enable unbiased local Jaccard estimation
Authors: Kille Bryce , Garrison Erik , Treangen Todd J , Phillippy Adam M 
Published: August 2023

Abstract

Motivation
The Jaccard similarity on k-mer sets has shown to be a convenient proxy for sequence identity. By avoiding expensive base-level alignments and comparing reduced sequence representations, tools such as MashMap can scale to massive numbers of pairwise comparisons while still providing useful similarity estimates. However, due to their reliance on minimizer winnowing, previous versions of MashMap were shown to be biased and inconsistent estimators of Jaccard similarity. This directly impacts downstream tools that rely on the accuracy of these estimates.

Results
To address this, we propose the minmer winnowing scheme, which generalizes the minimizer scheme by use of a rolling minhash with multiple sampled k-mers per window. We show both theoretically and empirically that minmers yield an unbiased estimator of local Jaccard similarity, and we implement this scheme in an updated version of MashMap. The minmer-based implementation is over 10 times faster than the minimizer-based version under the default ANI threshold, making it well-suited for large-scale comparative genomics applications.

Availability and implementation
MashMap3 is available at https://github.com/marbl/MashMap.
BJS 1 The impact of postoperative complications on quality of life after major abdominal surgery: An analysis of the Perioperative Quality Improvement database
Authors: Downey Candice , Bainbridge Jamie , Jayne David , Meads David 
Published: August 2023

Abstract

Aims
Postoperative complications are common, but there are limited data regarding their implications on patients’ quality of life. This work aimed to address this gap in the literature by analysing prospectively collected, high quality data to estimate the impact of postoperative complications on patients’ health-related quality of life.

Methods
Data from the Perioperative Quality Improvement Programme were analysed and included patient-level data for 19,685 adults who underwent elective major abdominal procedures in England since 2016. Postoperative complications were classified using the Clavien-Dindo classification system. Quality of life was assessed by responses to the EuroQol-5-dimension five-levels of response (EQ-5D-5L) questionnaire before surgery, and at 6 and 12 months post-surgery. Ordinal logistic regression estimated the association between Clavien-Dindo grades and quality of life.

Results
At six and twelve months post-surgery, increasingly severe postoperative complications were significantly associated with lower health-related quality of life. The effect of postoperative complications on quality of life was sustained until at least twelve months post-surgery. Between admission and twelve months post-surgery, 0.012, 0.026, 0.033, and 0.086 QALYs were lost for those experiencing a Grade I, II, III, or IV postoperative complication, respectively.

Conclusions
This is the first large-scale study of major abdominal surgery to evaluate the effect of postoperative complications on patients’ quality of life after surgery, and to provide utility values for postoperative complications using the Clavien-Dindo classification system. This work enables robust cost-utility analyses of interventions in future surgical research, and outlines the value case for research to predict, prevent and manage postoperative complications.
SUS 1 Indications for day one postoperative blood tests after emergency appendicectomy
Authors: Kho Jason , Kuan Jen Yee , Derbyshire Charles , Ward Jeremy , Rajendran Ilayaraja 
Published: August 2023

Abstract

Aim
Appendicitis accounts for 47,000 admissions/year in England, and commonly involves patients aged 10 to 65 years. A cost-effectiveness study was conducted to assess the need for routine day-one postoperative (D1) blood tests following emergency appendicectomy (EA).

Method
Retrospective review of all EAs was carried out between January 2022 and October 2022. Data was collected from local hospital database. Elective appendicectomies were excluded. D1 blood tests were deemed necessary in complicated EAs, with clear documentation of the indication for blood tests. Costs of blood samples (FBC=£12, U&E, LFT and bone profile=£23 and CRP=£12) were verified by local/national (NICE and CCG) sources.

Results
Fifty EAs were reviewed. 39 (78%) cases were completed laparoscopically, 9 (18%) were laparoscopic converted to open and 2 (4%) were open appendicectomies. 36/50 (72%) patients had D1 bloods, 30 (83%) of which had an uncomplicated recovery. 6 (17%) patients developed postoperative complications; diabetic ketoacidosis (DKA) (n=1), ileus (n=2), superficial wound dehiscence (n=1) and infected intra-abdominal collection diagnosed two weeks post-op (n=2) (one patient was managed conservatively with intravenous antibiotics and the other underwent radiological-guided drainage). Only 1 (2%) patient (postoperative DKA) had a clear clinical indication for D1 bloods. This translates to potential cost savings of £2350.

Conclusion
Study demonstrates potential significant cost savings if clinicians rationalise blood test requests following EAs. These findings may be extended to other emergency and elective cases. In a resource-constrained environment, it is worth considering the need for postoperative tests, which could influence length of hospital stay and further cost savings.
SUS 2 Telemedicine for diagnosis of Surgical Site Infection (SSI): Feasible, safe and sustainable
Authors: Lathan Ross , Kwan Jing Yi , Smith George , Chetter Ian , Lockwood Sonia , Yiasemidou Marina 
Published: August 2023

Abstract

Background
In 2019, the NHS contributed to around 25 million tonnes of CO2 equivalent, equating to around 7% of the total UK carbon footprint (CO2e) that year. A significant contributor is CO2e attributable to patient travel, which has almost doubled since 1990.

Aim
To assess the feasibility and sustainability of telemedicine for diagnosis of SSI.

Methods
Patients were reviewed remotely at 30 days with a combined outcome measure (photographs and validated questionnaire). If wound complications were identified, face-to-face review or remote management were arranged. The SusQI method of emissions calculations were used with DEFRA conversion factors based on the minimal material and equipment usage and cost in clinic. Patient postcodes were applied to conversion factors based upon mode of travel to calculate kgCO2e for patient travel. Total CO2e per remote review were subtracted from the model clinic emissions for potential savings.

Results
25 patients (M:F 1.78, 65.1±11.1 years) were reviewed remotely. The median return distance for patient travel was 26.4 miles (3.4-71.4 miles). The estimated CO2e of clinic was 13.1kgCO2e per patient. Mean emissions per patient travel was 9.7kgCO2e, giving the average simple clinic carbon footprint of 22.8 kgCO2e. Mean carbon footprint of remote follow-up was 0.47kgCO2e per patient, estimating the potential savings at 22.3kgCO2e. Four patients had wound infections, but were diagnosed and managed remotely.

Conclusions
This model shows that implementation of an asynchronous digital follow-up model is effective in substantially reducing carbon footprint of a tertiary surgical centre.