bluuebunny/crossref_metadata_2025 huggingface dataset:
Systematic multi-scale decomposition of ocean variability using machine learning
Authors: Franzke Christian L. E. , Gugole Federica , Juricke Stephan
Published: July 2022

Multi-scale systems, such as the climate system, the atmosphere, and the ocean, are hard to understand and predict due to their intrinsic nonlinearities and chaotic behavior. Here, we apply a physics-consistent machine learning method, the multi-resolution dynamic mode decomposition (mrDMD), to oceanographic data. mrDMD allows a systematic decomposition of high-dimensional data sets into time-scale dependent modes of variability. We find that mrDMD is able to systematically decompose sea surface temperature and sea surface height fields into dynamically meaningful patterns on different time scales. In particular, we find that mrDMD is able to identify varying annual cycle modes and is able to extract El Nino–Southern Oscillation events as transient phenomena. mrDMD is also able to extract propagating meanders related to the intensity and position of the Gulf Stream and Kuroshio currents. While mrDMD systematically identifies mean state changes similarly well compared to other methods, such as empirical orthogonal function decomposition, it also provides information about the dynamically propagating eddy component of the flow. Furthermore, these dynamical modes can also become progressively less important as time progresses in a specific time period, making them also state dependent.
Precise measurement of correlation parameters driving optical transparency in CaVO3 thin film by steady state and time resolved terahertz spectroscopy
Authors: Anagha P. , Kinha Monu , Khare Amit , Rana D. S.
Published: July 2022

Transparent conducting materials are inevitable in the fast-developing optoelectronic and photovoltaic industries. Correlated metals are emerging classes of materials that possess a charge density comparable to the metals in which the correlation effects provide transparency. So, understanding the fundamental physics of these materials is equally important to improve the performance of devices. We have investigated the low energy and non-equilibrium dynamics of the CaVO3 (CVO) thin film using terahertz time-domain and time-resolved terahertz spectroscopic measurements. Though the electrical resistivity of the CVO thin film shows a Fermi liquid-like signature, the terahertz conductivity dynamics unveil the presence of metal-insulator transition. Furthermore, the mass renormalization effects indicate the competition between electron correlations and phonon interactions in driving the ground state of this system. It is clear that the relaxation of photo-excited carriers is through electron–phonon thermalization, and comprehensive studies show the metallic nature of the system with electron correlations. Thus, the extracted optical and electrical parameters of CVO are comparable with the existing transparent conducting materials and, hence, make this system another potential candidate for transparent electronics.
Li3InCl6-coated LiCoO2 for high-performance all solid-state batteries
Authors: Zheng Xiu , Fu En-De , Chen Peng , Liu Sheng , Li Guo-Ran , Gao Xue-Ping
Published: July 2022

Halide solid electrolytes (HSEs) could be coated on high-voltage oxide cathodes at molecular-level via a solution process, which is highly favorable for reducing the interface impedance. However, during the preparation of composite cathodes, hydrate intermediates of HSEs are easily hydrolyzed to produce inactive impurities. In this work, the vacuum drying assisted method facilitates the generation of pure Li3InCl6 (LIC) on the surface of LiCoO2 (LCO) to improve the electrolyte/electrode solid–solid interface as well as the electrochemical stability of solid electrolyte under high voltage. By introducing Li7P3S11 as an anode buffer layer, 30 wt. %-LIC-coated LCO demonstrates high specific capacity of 121.7 mAh g−1 and good cycling stability. Our study highlights a promising method to build advanced composite cathodes for all-solid-state batteries.
Tunable coupling of widely separated superconducting qubits: A possible application toward a modular quantum device
Authors: Zhao Peng , Zhang Yingshan , Xue Guangming , Jin Yirong , Yu Haifeng
Published: July 2022

In addition to striving to assemble more and more qubits in a single monolithic quantum device, taking a modular design strategy may mitigate numerous engineering challenges for achieving large-scalable quantum processors with superconducting qubits. Nevertheless, a major challenge in the modular quantum device is how to realize high-fidelity entanglement operations on qubits housed in different modules while preserving the desired isolation between modules. In this work, we propose a conceptual design of a modular quantum device, where nearby modules are spatially separated by centimeters. In principle, each module can contain tens of superconducting qubits and can be separately fabricated, characterized, packaged, and replaced. By introducing a bridge module between nearby qubit modules and taking the coupling scheme utilizing a tunable bus, tunable coupling of qubits that are housed in nearby qubit modules could be realized. Given physically reasonable assumptions, we expect that sub-100-ns two-qubit gates for qubits housed in nearby modules, which are spatially separated by more than two centimeters could be obtained. In this way, the inter-module gate operations are promising to be implemented with gate performance comparable with that of intra-module gate operations. Moreover, with the help of through-silicon vias technologies, this long-range coupling scheme may also allow one to implement inter-module couplers in a multi-chip stacked processor. Thus, the tunable longer-range coupling scheme and the proposed modular architecture may provide a promising foundation for solving challenges toward large-scale quantum information processing with superconducting qubits.
Terahertz photodetection in scalable single-layer-graphene and hexagonal boron nitride heterostructures
Authors: Asgari M. , Viti L. , Balci O. , Shinde S. M. , Zhang J. , Ramezani H. , Sharma S. , Meersha A. , Menichetti G. , McAleese C. , Conran B. , Wang X. , Tomadin A. , Ferrari A. C. , Vitiello M. S.
Published: July 2022

The unique optoelectronic properties of single layer graphene (SLG) are ideal for the development of photonic devices across a broad range of frequencies from x rays to microwaves. In the terahertz (THz) frequency range (0.1–10 THz), this has led to the development of optical modulators, nonlinear sources, and photodetectors with state-of-the-art performances. A key challenge is the integration of SLG-based active elements with pre-existing technological platforms in a scalable way, while maintaining performance level unperturbed. Here, we report room temperature THz detectors made of large-area SLG, grown by chemical vapor deposition (CVD) and integrated in antenna-coupled field effect transistors. We selectively activate the photo-thermoelectric detection dynamics, and we employ different dielectric configurations of SLG on Al2O3 with and without large-area CVD hexagonal boron nitride capping to investigate their effect on SLG thermoelectric properties underpinning photodetection. With these scalable architectures, response times ∼5 ns and noise equivalent powers (NEPs) ∼1 nW Hz−1/2 are achieved under zero-bias operation. This shows the feasibility of scalable, large-area, layered material heterostructures for THz detection.
Reynolds number effect of the turbulent micropolar channel flow
Authors: Sofiadis G. , Sarris I.
Published: July 2022

The turbulent regime of non-Newtonian flows presents a particular interest as flow behavior is directly affected by the internal microstructure type of the fluid. Differences in the dispersed phase of a particle laden flow can either lead to drag reduction and turbulence attenuation or to drag and turbulence enhancement in polymer flows and dense suspensions, respectively. A general concept of non-Newtonian fluid flow may be considered in a continuous manner through the micropolar theory, recognizing the limitations that bound this theory. In recent articles [Sofiadis and Sarris, “Microrotation viscosity effect on turbulent micropolar fluid channel flow,” Phys. Fluids 33, 095126 (2021); Sofiadis and Sarris, “Turbulence intensity modulation by micropolar fluids,” Fluids 6, 195 (2021)], the micropolar viscosity effect of the turbulent channel flow under constant Reynolds number and its turbulent modulation were investigated. The present study focuses on the investigation of the turbulent micropolar regime as the Reynolds number increases in a channel flow. Findings support that the micropolar stress, which was found to assist turbulence enhancement in the present model, attenuates as Re increases. Effects on the friction behavior of the flow, as Reynolds number increases, become more important for cases of higher micropolar viscosity, where a reverse drag behavior is observed as compared to lower micropolar viscosity ones. Finally, turbulence intensification for these cases declines close to the wall in contrast to lower micropolar viscosity flows, which manage to sustain high turbulence and increase drag in the near-wall region along with Re.
Fractional SEIR model and data-driven predictions of COVID-19 dynamics of Omicron variant
Authors: Cai Min , Em Karniadakis George , Li Changpin
Published: July 2022

We study the dynamic evolution of COVID-19 caused by the Omicron variant via a fractional susceptible–exposed–infected–removed (SEIR) model. Preliminary data suggest that the symptoms of Omicron infection are not prominent and the transmission is, therefore, more concealed, which causes a relatively slow increase in the detected cases of the newly infected at the beginning of the pandemic. To characterize the specific dynamics, the Caputo–Hadamard fractional derivative is adopted to refine the classical SEIR model. Based on the reported data, we infer the fractional order and time-dependent parameters as well as unobserved dynamics of the fractional SEIR model via fractional physics-informed neural networks. Then, we make short-time predictions using the learned fractional SEIR model.
Nonadiabatic molecular dynamics simulations based on time-dependent density functional tight-binding method
Authors: Wu Xiaoyan , Wen Shizheng , Song Huajing , Frauenheim Thomas , Tretiak Sergei , Yam ChiYung , Zhang Yu
Published: July 2022

Nonadiabatic excited state molecular dynamics underpin many photophysical and photochemical phenomena, such as exciton dynamics, and charge separation and transport. In this work, we present an efficient nonadiabatic molecular dynamics (NAMD) simulation method based on time-dependent density functional tight-binding (TDDFTB) theory. Specifically, the adiabatic electronic structure, an essential NAMD input, is described at the TDDFTB level. The nonadiabatic effects originating from the coupled motions of electrons and nuclei are treated by the trajectory surface hopping algorithm. To improve the computational efficiency, nonadiabatic couplings between excited states within the TDDFTB method are derived and implemented using an analytical approach. Furthermore, the time-dependent nonadiabatic coupling scalars are calculated based on the overlap between molecular orbitals rather than the Slater determinants to speed up the simulations. In addition, the electronic decoherence scheme and a state reassigned unavoided crossings algorithm, which has been implemented in the NEXMD software, are used to improve the accuracy of the simulated dynamics and handle trivial unavoided crossings. Finally, the photoinduced nonadiabatic dynamics of a benzene molecule are simulated to demonstrate our implementation. The results for excited state NAMD simulations of benzene molecule based on TDDFTB method compare well to those obtained with numerically expensive time-dependent density functional theory. The proposed methodology provides an attractive theoretical simulation tool for predicting the photophysical and photochemical properties of complex materials.
Large-eddy simulation of the compressible flows around a wavy-axis square cylinder
Authors: Xu Chang-Yue , Wang Bin , Liu Hao , Men Yuan , Sun Jian-Hong
Published: July 2022

The compressible flows past a wavy-axis square cylinder are numerically carried out by means of the large-eddy simulation technique for two different free-stream Mach numbers (M∞=0.71 and 0.85), which are less than the critical Mach number Mcr (≈0.9). The Reynolds number based on the side-length of the wavy-axis square cylinder is chosen as 4×105. For comparison, the compressible flows around the corresponding normal square cylinder are also calculated. The control effects and mechanisms are systematically analyzed. Comparing the wavy-axis square cylinder with a normal square cylinder for M∞=0.71 and 0.85, about 23.5% and 8.1% drag reductions are acquired, respectively, and the fluctuating forces are suppressed significantly. Based on the analysis of drag decomposition, when M∞<Mcr, the drag reduction related to vortex force prevails over that relevant to compressible effect. Moreover, the wavy-axis square cylinder can also provide the effective control for type C moving shock. The effective drag reduction and suppression of fluctuating force obtained by the wavy-axis square cylinder are closely associated with the higher base-pressure and lower turbulent fluctuations in the near wake, which can be achieved by the strengthened compressibility and waviness effect of shear-layer. However, when M∞ approaches Mcr, the effective flow control from the wavy-axis square cylinder is attenuated due to the competition between strengthened compressibility and the waviness effect of the shear-layer.
Phantom scalar field counterpart to Curzon–Chazy spacetime
Authors: Polcar Lukáš , Svítek Otakar
Published: July 2022

We derive and analyze phantom scalar field counterpart to Curzon–Chazy spacetime. Such solution contains a wormhole throat while the region inside the throat behaves like a one-directional time machine. We describe its conformal structure and non-scalar singularity hidden inside the wormhole. We examine the results provided by different definitions of mass of the spacetime to understand their value in the presence of phantom matter. The electromagnetic generalization of this spacetime is as well briefly considered.
Magnetic ground state of supported monatomic Fe chains from first principles
Authors: Nagyfalusi B , Udvardi L , Szunyogh L
Published: July 2022

A new computational scheme is presented based on a combination of the conjugate gradient and the Newton–Raphson method to self-consistently minimize the energy within local spin-density functional theory, thus to identify the ground state magnetic order of a finite cluster of atoms. The applicability of the new ab initio optimization method is demonstrated for Fe chains deposited on different metallic substrates. The optimized magnetic ground states of the Fe chains on Rh(111) are analyzed in details and a good comparison is found with those obtained from an extended Heisenberg model containing first principles based interaction parameters. Moreover, the effect of the different bilinear spin–spin interactions in the formation of the magnetic ground states is monitored. In case of Fe chains on Nb(110) spin-spiral configurations with opposite rotational sense are found as compared to previous spin-model results which hints on the importance of higher order chiral interactions. The wavelength of the spin-spiral states of Fe chains on Re(0001) was obtained in good agreement with scanning tunneling microscopy experiments.
High-pressure melting experiments of Fe3S and a thermodynamic model of the Fe–S liquids for the Earth’s core
Authors: Thompson Samuel , Sugimura-Komabayashi Emiko , Komabayashi Tetsuya , McGuire Chris , Breton Helene , Suehiro Sho , Ohishi Yasuo
Published: July 2022

Melting experiments on Fe3S were conducted to 75 GPa and 2800 K in laser-heated and internally resistive-heated diamond anvil cells with in-situ x-ray diffraction and/or post-mortem textural observation. From the constrained melting curve, we assessed the thermal equation of state for Fe3S liquid. Then we constructed a thermodynamic model of melting of the system Fe–Fe3S including the eutectic relation under high pressures based on our new experimental data. The mixing properties of Fe–S liquids under high pressures were evaluated in order to account for existing experimental data on eutectic temperature. The results demonstrate that the mixing of Fe and S liquids are nonideal at any core pressure. The calculated sulphur content in eutectic point decreases with increasing pressure to 120 GPa and is fairly constant of 8 wt% at greater pressures. From the Gibbs free energy, we derived the parameters to calculate the crystallising point of an Fe–S core and its isentrope, and then we calculated the density and the longitudinal seismic wave velocity (Vp) of these liquids along each isentrope. While Fe3S liquid can account for the seismologically constrained density and Vp profiles over the outer core, the density of the precipitating phase is too low for the inner core. On the other hand, a hypothetical Fe–S liquid core with a bulk composition on the Fe-rich side of the eutectic point cannot represent the density and Vp profiles of the Earth’s outer core. Therefore, Earth’s core cannot be approximated by the system Fe–S and it should include another light element.
Diagnosis method based on hidden Markov model and Weibull mixture model for mechanical faults of in-wheel motors
Authors: Xue Hongtao , Liu Bingchen , Ding Dianyong , Zhou Jiawen , Cui Xiaoli
Published: July 2022

To effectively monitor the operation state of in-wheel motors used in electric vehicles and ensure the safety of the whole vehicle, a diagnosis method based on hidden Markov model (HMM) and Weibull mixture model (WMM) is proposed for mechanical faults in in-wheel motors, known simply as the WMM-HMM diagnosis method. Firstly, vibration signals of the in-wheel motor are extracted for sensitive symptom parameters which are used to characterize the operation state and establish the observation sequence. Secondly, WMM is employed to expand the limited observation sequence under various operating states of in-wheel motors to obtain sufficient observation sequence as the training sample set of HMM, and HMM parameters are determined through combining supervised learning with unsupervised learning algorithm. Then the WMM-HMM diagnosis models are constructed under low and medium speed conditions respectively. Finally, the corresponding faults in-wheel motors are customized and the test bench is built to verify the proposed method. The test results show that the proposed method can accurately identify the mechanical fault state of in-wheel motors under different conditions and has good generalization and applicability in traditional methods comparison.
Beam position monitor design for the High Energy Photon Source
Authors: He Jun , Sui Yanfeng , Li Yong , Ma Huizhou , Du Yaoyao , Zhao Ying , Zhang Wan , Wei Shujun , Xu Taoguang , Yue Junhui , Cao Jianshe
Published: July 2022

A button and stripline beam position monitor (BPM) were designed and developed to achieve sub-micron orbit stability in the High Energy Photon Source (HEPS). Analytical formulae and CST electromagnetic simulation software were used to calculate the radio frequency characteristics of the BPM. The BPM design procedure was developed according to the HEPS requirements. The characteristic impedances of the stripline were designed to be 50 Ω and confirmed by measurements. The position sensitivity, position resolution, capacitance, and wakefield impedance of the button BPM were calculated. The measurement results confirmed that the design satisfied the HEPS requirements.
Utilization of coupled eigenmodes in Akiyama atomic force microscopy probes for bimodal multifrequency sensing
Authors: Kort-Kamp Wilton J M , Murdick Ryan A , Htoon Han , Jones Andrew C
Published: July 2022

Akiyama atomic force microscopy probes represent a unique means of combining several of the desirable properties of tuning fork and cantilever probe designs. As a hybridized mechanical resonator, the vibrational characteristics of Akiyama probes result from a complex coupling between the intrinsic vibrational eigenmodes of its constituent tuning fork and bridging cantilever components. Through a combination of finite element analysis modeling and experimental measurements of the thermal vibrations of Akiyama probes we identify a complex series of vibrational eigenmodes and measure their frequencies, quality factors, and spring constants. We then demonstrate the viability of Akiyama probes to perform bimodal multi-frequency force sensing by performing a multimodal measurement of a surface’s nanoscale photothermal response using photo-induced force microscopy imaging techniques. Further performing a parametric search over alternative Akiyama probe geometries, we propose two modified probe designs to enhance the capability of Akiyama probes to perform sensitive bimodal multifrequency force sensing measurements.
Copper phyllosilicate-derived ultrafine copper nanoparticles with plenty of Cu0 and Cu+ for the enhanced catalytic performance of ethylene carbonate hydrogenation to methanol
Authors: Li Huabo , Cui Yuanyuan , Liu Yixin , Wang Songlin , Dai Wei-Lin
Published: July 2022

The hydrogenation of CO2-derived carbonates to methanol is an alternative route for the indirect utilization of abundant C1 sources. Various Cu/SiO2 catalysts with different copper loading content prepared by using an ammonia evaporation hydrothermal method are implemented to evaluate the catalytic performance of ethylene carbonate (EC) hydrogenation to methanol and ethylene glycol (EG). The Cu loading content was identified to significantly affect the Cu nanoparticles (NPs) size and metal-support interaction. Highly dispersed Cu NPs restricted and embedded in copper phyllosilicate presented a smaller average particle size than the impregnated Cu/SiO2–IM catalyst. The xCu/SiO2 catalyst with ultrafine Cu NPs showed abundant Cu–O–Si interfaces, acidic sites, and coherent Cu0 and Cu+ species. The 5Cu/SiO2 catalyst achieved methanol yield of 76% and EG yield of 98% at EC conversion of 99%, and no obvious deactivation was observed after long-term operation. The superior catalytic performance of the 5Cu/SiO2 catalyst is attributed to the synergetic effect between the appropriate Cu0 surface area which provides sufficient active hydrogen, and the atomic ratio of Cu+ for the polarization and activation of carbon–oxygen bonds.
Detecting beats in the photoplethysmogram: benchmarking open-source algorithms
Authors: Charlton Peter H , Kotzen Kevin , Mejía-Mejía Elisa , Aston Philip J , Budidha Karthik , Mant Jonathan , Pettit Callum , Behar Joachim A , Kyriacou Panicos A
Published: July 2022

The photoplethysmogram (PPG) signal is widely used in pulse oximeters and smartwatches. A fundamental step in analysing the PPG is the detection of heartbeats. Several PPG beat detection algorithms have been proposed, although it is not clear which performs best. Objective: This study aimed to: (i) develop a framework with which to design and test PPG beat detectors; (ii) assess the performance of PPG beat detectors in different use cases; and (iii) investigate how their performance is affected by patient demographics and physiology. Approach: Fifteen beat detectors were assessed against electrocardiogram-derived heartbeats using data from eight datasets. Performance was assessed using the F
1 score, which combines sensitivity and positive predictive value. Main results: Eight beat detectors performed well in the absence of movement with F
1 scores of ≥90% on hospital data and wearable data collected at rest. Their performance was poorer during exercise with F
1 scores of 55%–91%; poorer in neonates than adults with F
1 scores of 84%–96% in neonates compared to 98%–99% in adults; and poorer in atrial fibrillation (AF) with F
1 scores of 92%–97% in AF compared to 99%–100% in normal sinus rhythm. Significance: Two PPG beat detectors denoted ‘MSPTD’ and ‘qppg’ performed best, with complementary performance characteristics. This evidence can be used to inform the choice of PPG beat detector algorithm. The algorithms, datasets, and assessment framework are freely available.
A systematic review of deep learning methods for modeling electrocardiograms during sleep
Authors: Sun Chenxi , Hong Shenda , Wang Jingyu , Dong Xiaosong , Han Fang , Li Hongyan
Published: July 2022

Sleep is one of the most important human physiological activities, and plays an essential role in human health. Polysomnography (PSG) is the gold standard for measuring sleep quality and disorders, but it is time-consuming, labor-intensive, and prone to errors. Current research has confirmed the correlations between sleep and the respiratory/circulatory system. Electrocardiography (ECG) is convenient to perform, and ECG data are rich in breathing information. Therefore, sleep research based on ECG data has become popular. Currently, deep learning (DL) methods have achieved promising results on predictive health care tasks using ECG signals. Therefore, in this review, we systematically identify recent research studies and analyze them from the perspectives of data, model, and task. We discuss the shortcomings, summarize the findings, and highlight the potential opportunities. For sleep-related tasks, many ECG-based DL methods produce more accurate results than traditional approaches by combining multiple signal features and model structures. Methods that are more interpretable, scalable, and transferable will become ubiquitous in the daily practice of medicine and ambient-assisted-living applications. This paper is the first systematic review of ECG-based DL methods for sleep tasks.
100 Gb/s High Throughput Serial Protocol (HTSP) for data acquisition systems with interleaved streaming
Authors: Ruckman L. , Doering D.
Published: July 2022

Demands on Field-Programmable Gate Array (FPGA) data transport
have been increasing over the years as frame sizes and
refresh rates increase. As the bandwidths requirements increase
the ability to implement data transport protocol layers
using “soft” programmable logic becomes harder and start to require harden
IP blocks implementation.
To reduce the number of physical links and interconnects, it is common for
data acquisition systems to require interleaving of streams on the same link
(e.g. streaming data and streaming register access).
This paper presents a way to leverage existing
FPGA harden IP blocks to achieve a robust, low latency 100 Gb/s
point-to-point link with minimal programmable logic overhead
geared towards the needs of data acquisition systems with interleaved streaming requirements.
Development of a high-temporal resolution neutron flux measurement system for the HL-2M tokamak
Authors: Zhang Jie , Zhang Yipo , Zhang Jinglong , Zhou Jianhang , Zhan Xuwen , Wen Zuowei , Cheng Shikui , Zhu Yuxuan , Yuan Guoliang , Liu Yuhang , Yang Qiulei , Chen Wei , Shi Zhongbing , Liu Yi , Xu Min
Published: July 2022

To enhance the understanding of the physics of energetic
ions in fusion plasma, a high-temporal resolution neutron flux
measurement (HTRNFM) system, which is equipped with a fast-neutron
scintillation detector embedded with ZnS:Ag phosphor, has been
developed for the HL-2M tokamak. It has a temporal resolution of
10 μs during conventional operations. Its dynamic range is
sufficiently wide for neutron flux measurements by adopting the
combination use of the scalar mode and the Campbell mode. Based on
the Monte Carlo calculations, the applicable count rate ranges of
both the scalar mode and the Campbell mode are respectively
0.1–10 Mcps and 10–200 Mcps. The performance validation of the
HTRNFM system has been performed by neutron flux measurements in
magnetohydrodynamic (MHD) quiet plasmas in the HL-2A tokamak. In
another plasma with abundant MHD instabilities, both the continuous
neutron flux decreases and the rapid neutron flux decreases caused
by different MHD instabilities are observed in a more detailed
manner for the first time with the HTRNFM system than with other
neutron flux measurement (NFM) systems that have a lower temporal
resolution of 1 ms. The HTRNFM system will serve as a powerful
diagnostic tool for research on energetic ion confinement quality in
the HL-2M tokamak.
Liquid nitrogen cooling, control and monitoring system for the ELIADE HPGe clover detectors at ELI-NP
Authors: Dhal A. , Ramirez F. , Suliman G. , Roman T. , Ciocan G. , Testov D. , Petcu C. , Tatulea B. , Ur C.A. , Balabanski D.L.
Published: July 2022

We present a liquid nitrogen (LN2) cooling station for
the high-purity germanium (HPGe) segmented clover detectors of the
ELI-NP Array of DEtectors
(ELIADE) spectrometer, including its associated filling control and
monitoring systems, all designed and built in-house at Extreme Light
Infrastructure - Nuclear Physics (ELI-NP), Măgurele,
Romania. The automated LN2 filling process is controlled by a
CompactRIO (cRIO) system from National Instruments through a custom
LabVIEW software used for monitoring both the internal germanium
crystal temperatures as well as the temperatures of external Pt100
sensors (used for detection of overflow of LN2 from detectors
during a filling process). The detectors are filled with LN2 by
opening their individual filling valves (which are mounted on the
cooling station) and the process is automatically stopped once an
overflow condition is fulfilled by the corresponding external Pt100
sensor located downstream. A twelve-hour cycle is used to
periodically fill all of the detector dewars and keep their
germanium crystals cool at all times. The associated Graphic User
Interface (GUI), Command Line Interface (CLI) and Text User
Interface (TUI) are used for both controlling and monitoring the
above mentioned process. Alert and warning email messages were also
enabled via the cRIO system so that users can be alerted in
real-time in the event of any cooling malfunction. In this way, any
issues related to the cyclic filling procedure, as well as any
abnormal observations regarding the germanium crystal temperatures
can be quickly and efficiently addressed before the detectors have a
chance to warm back up to room temperature. Temperature data of all
the Pt100 sensors corresponding to detectors as well as to the
solenoid valves are made available in an influx database by the cRIO
control system. The web application Grafana access the database and
plots them in real-time for online monitoring.
Citizen science and geomorphology: the citizenMorph pilot system for observing and reporting data on landforms
Authors: Hennig Sabine , Abad Lorena , Hölbling Daniel , Tiede Dirk
Published: July 2022

Contributory citizen science projects face challenges regarding data quantity and quality. To counteract this, the projects must be centred around citizen needs and preferences, while considering aspects such as the data contribution process, including instructions, project promotion, information provision, feedback and recognition, and the design of the respective elements. Based on an understanding of the relevance of these issues affecting data contribution systems, we must determine which elements we can use to meet citizens’ needs and preferences and how to better tailor the system design to citizens’ requirements. The citizenMorph project, which aimed to create a pilot system for citizens to collect and report data on landforms, focused on the development of a citizen-centric system with elements that foster and encourage citizen engagement. We used a specifically conceived development workflow that combined participatory design with the prototyping model to involve citizen representatives in different ways and to different degrees in requirement specification, system design and implementation, and testing. This allowed citizens’ requirements to be specified and comprehensively considered in the citizenMorph system. Based on the input of citizens who were involved in the development process, the citizenMorph pilot system includes a data contribution application and a project-related website with several project-specific elements that focus on attracting and recruiting citizens to participate and increase their initial and ongoing engagement and willingness to report landform data. This includes traditional and web-based promotion elements, a specifically designed information strategy that considers information detail, depth and presentation media, project and task-tailored data contribution instructions and support, and the possibility for users to find and view the data they contributed on a web map.
Forest loss is significantly higher near clustered small dams than single large dams per megawatt of hydroelectricity installed in the Brazilian Amazon
Authors: Nickerson Samuel , Chen Gang , Fearnside Philip M , Allan Craig J , Hu Tongxi , de Carvalho Luis M T , Zhao Kaiguang
Published: July 2022

Hydropower in the Brazilian Amazon is a prevalent form of development, but dams have widespread and long-term environmental impacts that include deforestation in the areas surrounding the dams. Small hydropower plants (SHPs) are often perceived as having reduced environmental impacts compared to the large ones. In Brazil, SHPs are licensed by state governments, which have less strict requirements than the federal environmental agency. Brazil’s definition of ‘small’ dams has grown with successive increases in the maximum installed capacity from 10 to 30 to 50 megawatts (MW). This expanding loophole has increased the attractiveness of investing in multiple small dams rather than a single large dam, with resulting proliferation of SHPs. Forest dynamics surrounding the clustered SHPs when compared to single large dams are not well documented. In this study, we capitalized on a dense time series of satellite images to quantify and compare forest loss in the regions (over 110 000 km2 in area) surrounding 15 SHPs and 7 large dams at multiple watershed and buffer scales in the Brazilian Amazon for nearly two decades (2000–2018). The landscapes containing SHP clusters had lower cumulative forest loss as compared to those with large dams. However, when deforestation and hydroelectric generating capacity were jointly considered (i.e. forest loss per megawatt installed), we discovered an opposite trend. The regions surrounding the SHP clusters exhibited significant impacts ranging from 1.9 to 2.5 times that of the regions surrounding large dams across 5 km to sub-basin scales. Due to the considerable consequences of SHPs on deforestation, we argue that the rapid expansion of small hydropower should be approached with caution and requires more stringent environmental assessments.
The SAGEX review on scattering amplitudes Chapter 1: Modern fundamentals of amplitudes
Authors: Brandhuber Andreas , Plefka Jan , Travaglini Gabriele
Published: July 2022

This chapter introduces the foundational concepts and techniques for scattering amplitudes. It is meant to be accessible to readers with only a basic understanding of quantum field theory. Topics covered include: the four-dimensional spinor-helicity formalism and the colour decomposition of Yang–Mills scattering amplitudes; the study of soft and collinear limits of Yang–Mills and gravity amplitudes; the BCFW recursion relation and generalised unitarity, also in the superamplitudes formalism of

N
=
4

supersymmetric Yang–Mills; an overview of standard and hidden symmetries of the S-matrix of

N
=
4

supersymmetric Yang–Mills, such as the conformal, dual conformal and Yangian symmetries; and a brief excursus on form factors of protected and non-protected operators in Yang–Mills theory. Several examples and explicit calculations are also provided.
Bayesian design of clinical trials using joint models for recurrent and terminating events
Authors: Xu Jiawei , Psioda Matthew A , Ibrahim Joseph G
Published: July 2022

Joint models for recurrent event and terminating event data are increasingly used for the analysis of clinical trials. However, few methods have been proposed for designing clinical trials using these models. In this article, we develop a Bayesian clinical trial design methodology focused on evaluating the effect of an investigational product (IP) on both recurrent event and terminating event processes considered as multiple primary endpoints, using a multifrailty joint model. Dependence between the recurrent and terminating event processes is accounted for using a shared frailty. Inferences for the multiple primary outcomes are based on posterior model probabilities corresponding to mutually exclusive hypotheses regarding the benefit of IP with respect to the recurrent and terminating event processes. We propose an approach for sample size determination to ensure the trial design has a high power and a well-controlled type I error rate, with both operating characteristics defined from a Bayesian perspective. We also consider a generalization of the proposed parametric model that uses a nonparametric mixture of Dirichlet processes to model the frailty distributions and compare its performance to the proposed approach. We demonstrate the methodology by designing a colorectal cancer clinical trial with a goal of demonstrating that the IP causes a favorable effect on at least one of the two outcomes but no harm on either.
Genetic mechanisms underlying brain functional homotopy: a combined transcriptome and resting-state functional MRI study
Authors: Zhao Han , Cai Huanhuan , Mo Fan , Lu Yun , Yao Shanwen , Yu Yongqiang , Zhu Jiajia
Published: July 2022

Functional homotopy, the high degree of spontaneous activity synchrony and functional coactivation between geometrically corresponding interhemispheric regions, is a fundamental characteristic of the intrinsic functional architecture of the brain. However, little is known about the genetic mechanisms underlying functional homotopy. Resting-state functional magnetic resonance imaging data from a discovery dataset (656 healthy subjects) and 2 independent cross-race, cross-scanner validation datasets (103 and 329 healthy subjects) were used to calculate voxel-mirrored homotopic connectivity (VMHC) indexing brain functional homotopy. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial correlation analysis was conducted to identify genes linked to VMHC. We found 1,001 genes whose expression measures were spatially associated with VMHC. Functional enrichment analyses demonstrated that these VMHC-related genes were enriched for biological functions including protein kinase activity, ion channel regulation, and synaptic function as well as many neuropsychiatric disorders. Concurrently, specific expression analyses showed that these genes were specifically expressed in the brain tissue, in neurons and immune cells, and during nearly all developmental periods. In addition, the VMHC-associated genes were linked to multiple behavioral domains, including vision, execution, and attention. Our findings suggest that interhemispheric communication and coordination involve a complex interaction of polygenes with a rich range of functional features.
Arrhythmogenesis of surgical atrial incisions and lesions in Maze procedure: insights from high-resolution mapping of atrial tachycardias
Authors: Hu Wei , Zhou Dongchen , Ding Xiangwei , Yang Gang , Liu Hailei , Wang Zidun , Chen Hongwu , Ju Weizu , Li Mingfang , Zhang Fengxiang , Yang Jian , Han Jie , Wu Xianhao , Qiu Zhaohui , Zheng Liangrong , Chen Minglong
Published: July 2022

Background

Atrial tachycardias (ATs) frequently develop after a surgical Maze procedure. We aimed to elucidate the electrophysiologic mechanisms and their arrhythmogenic substrates of these ATs.

Methods and results

We retrospectively reviewed 20 patients (14 females, mean age of 55.5 ± 8.6 years) with post-Maze ATs who underwent high-resolution mapping at three institutions. The slow conduction areas, reentry circuits, voltage signals, complex electrograms, and their correlation with the surgical incisions and lesions placed in the surgical Maze procedures were analyzed. Thirty-six ATs with a mean cycle length of 260.0 ± 67.6 ms were mapped in these patients. Among them, 22 (61.1%) were anatomical macro-reentrant ATs (AMAT), 12 (33.3%) non-AMATs (localized ATs), and 2 (5.6%) focal ATs, respectively. Epicardial conduction bridges were observed in 6/20 (30.0%) patients and 7/36 (19.4%) ATs. Different arrhythmogenic substrates were identified in these ATs, including slow conduction regions within the previous lesion areas or between the incisions and anatomical structures, the prolonged activation pathways caused by the short lesions connecting the tricuspid annulus, and the circuits around the long incisions and/or lesions.

Conclusions

Reentry is the main mechanism of the post-Maze ATs. The pro-arrhythmic substrates are most likely caused by surgical incisions and lesions. The slow conduction regions and the protected channels yielded from these areas are the major arrhythmogenic factors.
A Characterisation of Virtually Free Groups via Minor Exclusion
Authors: Khukhro Ana
Published: July 2022

We give a new characterisation of virtually free groups using graph minors. Namely, we prove that a finitely generated, infinite group is virtually free if and only if for any finite generating set, the corresponding Cayley graph is minor excluded. This answers a question of Ostrovskii and Rosenthal. The proof relies on showing that a finitely generated group that is minor excluded with respect to every finite generating set is accessible, using a graph-theoretic characterisation of accessibility due to Thomassen and Woess.
Evaluation of a diagnostic algorithm for rapid identification of Gram-negative species and detection of extended-spectrum β-lactamase and carbapenemase directly from blood cultures
Authors: Comini Sara , Bianco Gabriele , Boattini Matteo , Banche Giuliana , Ricciardelli Guido , Allizond Valeria , Cavallo Rossana , Costa Cristina
Published: July 2022

Objectives

To evaluate a rapid diagnostic algorithm based on MALDI-TOF MS, lateral flow immunoassays (LFIAs) and molecular testing performed directly from positive blood cultures (BCs) for Gram-negative species identification and detection of CTX-M extended-spectrum β-lactamases and main carbapenemases.

Methods

Non-duplicate BCs positive to Gram-negative bacteria at microscope examination were subjected to species identification by direct MALDI-TOF MS following recovery of bacterial pellet by Rapid MBT Sepsityper® kit. Subsequently, NG-Test® CARBA 5 and NG-Test® CTX-M MULTI LFIAs were performed according to identified microbial species. Eazyplex® SuperBug CRE molecular assay was performed in cases of NG-Test® CARBA 5 negative results in patients with documented carbapenemase-producers carriage. Results of rapid diagnostic workflow were compared with those obtained by conventional diagnostic routine.

Results

Overall, the direct MALDI-TOF MS protocol allowed reliable identification to the species level of 92.1% of the 2133 monomicrobial BCs. Rate of matched identification was significantly higher for Enterobacterales (97.3%) in comparison to non-fermenting Gram-negative species (80.2%), obligate anaerobic bacteria (42.1%) and fastidious Gram-negative species (41.5%). The overall sensitivity of NG-Test® CARBA 5 and NG-Test® CTX-M MULTI was 92.2% and 91.6%, respectively. Integration of Easyplex® SuperBug CRE allowed the detection of blaKPC mutants associated with ceftazidime/avibactam resistance, reaching 100% sensitivity in carbapenemase detection. Both LFIAs and molecular testing showed no false-positive results.

Conclusions

Algorithms based on MALDI-TOF MS, LFIAs and molecular testing may represent a cost-effective tool to timely identify Gram-negative species and detect resistance markers directly from BCs. According to local epidemiology, these results may allow antimicrobial stewardship interventions including prompt use of new approved drugs.
Cycles of regional innovative growth
Authors: Esposito Christopher R
Published: July 2022

For academics and policymakers invested in regional economic development, two pertinent questions are how innovative city-regions rise and whether it is inevitable that innovative city-regions will fall. Using data from 8 million patents granted to U.S.-based inventors between 1850 and 1999, this study describes a general process that city-regions undergo as innovation begins, expands, declines and (sometimes) resurges in regions. The results of the study show that inventors experiment with a small number of promising, diverse and non-local ideas in the years before innovation in their home regions begins to grow, that inventors build on early locally introduced ideas as innovation in their home regions expands, and that inventors experiment with relatively homogeneous sets of ideas shortly before innovation in their home regions declines. The results also show that declining U.S. city-regions rarely experience second waves of local innovative growth. However, when they do experience second waves, those waves are anticipated by changes in the knowledge sourcing strategies of local inventors. In particular, the years leading up to second cycles of regional innovative growth, local inventors experiment with promising, diverse and non-local ideas.
Recovery of Partially Engorged Haemaphysalis longicornis (Acari: Ixodidae) Ticks from Active Surveillance
Authors: Price Keith J , Witmier Bryn J , Eckert Rebecca A , Boyer Christian N
Published: July 2022

The invasive Asian longhorned tick, Haemaphysalis longicornis, has rapidly spread across the northeastern United States and is associated with pathogens of public health and veterinary concern. Despite its importance in pathogen dynamics, H. longicornis blood-feeding behavior in nature, specifically the likelihood of interrupted feeding, remains poorly documented. Here, we report the recovery of partially engorged, questing H. longicornis from active tick surveillance in Pennsylvania. Significantly more engorged H. longicornis nymphs (1.54%) and adults (3.07%) were recovered compared to Ixodes scapularis nymphs (0.22%) and adults (zero). Mean Scutal Index difference between unengorged and engorged nymph specimens was 0.65 and 0.42 for I. scapularis and H. longicornis, respectively, suggesting the questing, engorged H. longicornis also engorged to a comparatively lesser extent. These data are among the first to document recovery of engorged, host-seeking H. longicornis ticks and provide initial evidence for interrupted feeding and repeated successful questing events bearing implications for pathogen transmission and warranting consideration in vector dynamics models.
Essential work and emergency childcare: identifying gender differences in COVID-19 effects on labour demand and supply
Authors: Meekes Jordy , Hassink Wolter H J , Kalb Guyonne
Published: July 2022

We examine whether the COVID-19 crisis affects women and men differently in terms of employment, working hours, and hourly wages, and whether the effects are demand or supply driven. COVID-19 impacts are studied using administrative data on all Dutch employees up to December 2020, focussing on the national lockdowns and emergency childcare for essential workers in the Netherlands. First, the impact of COVID-19 is much larger for non-essential workers than for essential workers. Although female non-essential workers are more affected than male non-essential workers, on average, women and men are equally affected, because more women than men are essential workers. Second, the impact for partnered essential workers with young children, both men and women, is not larger than for others. Third, single-parent essential workers respond with relatively large reductions in labour supply, suggesting emergency childcare was insufficient for them. Overall, labour demand effects appear larger than labour supply effects.