bluuebunny/crossref_metadata_2025 huggingface dataset:
Radiation of relativistic ‘harmonic’ oscillator
Authors: Bogdanova J , Epp V , Yakovlev I
Published: August 2022

Dynamics and radiation of a relativistic charged particle moving in a linear restoring force field is studied. Solutions to the equations of motion are presented in a compact form in terms of Jacobi elliptic functions. The intensity of radiation, its angular distribution and radiation spectrum of a relativistic oscillator are investigated. It is shown that, unlike a non-relativistic oscillator, the maximum intensity is emitted not at the turning points, but at some intermediate points of the particle’s trajectory. The emission spectrum consists of lines at frequencies that are multiples of the oscillation frequency of the oscillator. As the oscillator energy increases, the number of harmonics in the spectrum increases. The maximum in the spectrum of highly relativistic oscillator occurs on high numbers of harmonics.
Fermionic superfluidity: from cold atoms to neutron stars
Authors: Lopez Annette , Kelly Patrick , Dauer Kaelyn , Vitali Ettore
Published: August 2022

From flow without dissipation of energy to the formation of vortices when placed within a rotating container, the superfluid state of matter has proven to be a very interesting physical phenomenon. Here we present the key mechanisms behind superfluidity in fermionic systems and apply our understanding to one of the most exotic systems in the universe: the superfluid interior of a neutron star. The extreme conditions of neutron stars prevent us from directly probing the internal superfluid properties, however, we can experimentally realize conditions resembling the interior through the use of cold atoms prepared in a laboratory and simulated on a computer. Key insights can be gained by simulating the neutron star superfluid using another system with analogous properties: a cold atomic Fermi gas. Computational physicists are leveraging the power of supercomputers to simulate interacting atomic systems with unprecedented accuracy. In this paper we provide a pedagogical introduction to the physics, guiding the reader through the major conceptual steps to understand the relation between cold atoms, superfluids, and neutron stars. We stress the surprising similarity between these systems, which stems from universality, a fundamental notion in many-body physics. These topics are available in advanced textbooks, but introductory materials are harder to come by; this paper is intended to fill the gap for curious undergraduate and graduate students. We will show how cold atoms can help us make significant strides towards understanding the exotic physics found deep within the universe.
Cavity nucleation in single-component homogeneous amorphous solids under negative pressure
Authors: Galimzyanov B N , Mokshin A V
Published: August 2022

Understanding the cavity formation and cavity growth mechanisms in solids has fundamental and applied importance for the correct determination of their exploitation capabilities and mechanical characteristics. In this work, we present the molecular dynamics simulation results for the process of homogeneous formation of nanosized cavities in a single-component amorphous metallic alloy. To identify cavities of various shapes and sizes, an original method has been developed, which is based on filling cavities by virtual particles (balls) of the same diameter. By means of the mean first-passage time analysis, it was shown that the cavity formation in an amorphous metallic melt is the activation-type process. This process can be described in terms of the classical nucleation theory, which is usually applied to the case of first order phase transitions. Activation energy, critical size and nucleation rate of cavities are calculated, the values of which are comparable with those for the case of crystal nucleation in amorphous systems.
Influence of the electron-vibration coupling on the interfacial charge transfer in organic solar cells: a simple quantum model
Authors: Jemaï Ghassen , Chika Khouloud , Jemaa Khabthani Jouda , Mayou Didier
Published: August 2022

In this paper, we analyze the influence of the electron-vibration interaction on the charge transfer process at the donor-acceptor interface in an organic solar cell. We present an essentially exact numerical analysis for a minimal model with only one vibration mode which is coupled to the charge transfer state. We show that the charge transfer state can be hot or cold depending on the parameters and in particular on the value of the energy of the lowest unoccupied molecular orbital on the donor side. We analyze also different regimes where electron–hole attraction or hybridization effects at the interface can modify the quantum yield of the transfer. We discuss also briefly the possible effects of the other vibration modes that are coupled to the charge either on the donor side or on the acceptor side.
A new experimental setup for time-resolved measurements of interactions between gas jets and flexible surfaces
Authors: Burkert Johannes , Schwarze Rüdiger
Published: August 2022

The purpose of this study was to present a new setup for time-resolved measurements of the interactions between gas jets and flexible surfaces. Such interactions are dominated by characteristic surface deformations and gas-driven surface waves. Previous works have studied the gas–surface interaction only in a sectional plane but not as a three-dimensional problem. In our setup, surface deformations and waves were generated by the impingement of a supersonic jet on a flexible surface made of a silicon membrane. The inlet pressure of the Laval nozzle was varied from 0.8 bar to 3 bar and the nozzle surface distance was set in the range of 30–120 mm with respect to the flat surface. The entire surface area and its behavior were recorded using a high-speed camera. The evaluation was based on the pixel intensity values of the recorded surface images during the jet impingement. A fast Fourier transformation was applied to the results to determine the dominant frequencies of surface movements in detail. From this, low- and high-frequency events on the surface can be derived. Correlations between the main process parameters, nozzle distance, nozzle inlet pressure and characteristic surface behavior were deduced and mapped.
Numerical investigation of current distributions around defects in high temperature superconducting CORC® cables
Authors: Teyber Reed , Marchevsky Maxim , Martinez Aurora Cecilia Araujo , Prestemon Soren , Weiss Jeremy , van der Laan Danko
Published: August 2022

High performance ReBCO magnet prototypes are typically monitored and protected with voltage measurements, however a variance in safe operating limits has been observed. A potential issue arises from current redistribution phenomena associated with unidentified defects in cables composed of ReBCO tapes. In this work, a network model is developed to simulate current and voltage distributions around defects in CORC® cables. The evolving network of conductor overlap is evaluated. Trends in CORC® operation at 77 K are presented, and it is shown that power dissipation in an I–V curve depends strongly on a third dimension of defect magnitude. The predictive tool is then coupled with a differential evolution algorithm to recommend optimal CORC® layering topologies based on reel-to-reel tape measurements. The developed model facilitates understanding of CORC® cable phenomena, and the results suggest high temperature superconducting magnet protection can be improved with cable and defect characterization efforts.
Combination projection synchronization of fractional-order complex dynamic networks with time-varying delay couplings and disturbances
Authors: Fang Jie , Wei Da , Yin NanNan , Yu PeiZhao , Liu Peng
Published: August 2022

In this paper, the problem of combination projection synchronization of fractional-order complex dynamic networks with time-varying delay couplings and external interferences is studied. Firstly, the definition of combination projection synchronization of fractional-order complex dynamic networks is given, and the synchronization problem of the drive-response systems is transformed into the stability problem of the error system. In addition, time-varying delays and disturbances are taken into consideration to make the network synchronization more practical and universal. Then, based on Lyapunov stability theory and fractional inequality theory, the adaptive controller is formulated to make the drive and response systems synchronization by the scaling factors. The controller is easier to realize because there is no time-delay term in the controller. At last, the corresponding simulation examples demonstrate the effectiveness of the proposed scheme.
High precision solutions to quantized vortices within Gross–Pitaevskii equation
Authors: Peng Hao-Hao , Deng Jian , Lou Sen-Yue , Wang Qun
Published: August 2022

The dynamics of vortices in Bose–Einstein condensates of dilute cold atoms can be well formulated by Gross–Pitaevskii equation. To better understand the properties of vortices, a systematic method to solve the nonlinear differential equation for the vortex to very high precision is proposed. Through two-point Padé approximants, these solutions are presented in terms of simple rational functions, which can be used in the simulation of vortex dynamics. The precision of the solutions is sensitive to the connecting parameter and the truncation orders. It can be improved significantly with a reasonable extension in the order of rational functions. The errors of the solutions and the limitation of two-point Padé approximants are discussed. This investigation may shed light on the exact solution to the nonlinear vortex equation.
QCD at finite temperature and density within the fRG approach: an overview
Authors: Fu Wei-jie
Published: August 2022

In this paper, we present an overview on recent progress in studies of QCD at finite temperature and densities within the functional renormalization group (fRG) approach. The fRG is a nonperturbative continuum field approach, in which quantum, thermal and density fluctuations are integrated successively with the evolution of the renormalization group (RG) scale. The fRG results for the QCD phase structure and the location of the critical end point (CEP), the QCD equation of state (EoS), the magnetic EoS, baryon number fluctuations confronted with recent experimental measurements, various critical exponents, spectral functions in the critical region, the dynamical critical exponent, etc, are presented. Recent estimates of the location of the CEP from first-principle QCD calculations within fRG and Dyson–Schwinger equations, which pass through lattice benchmark tests at small baryon chemical potentials, converge in a rather small region at baryon chemical potentials of about 600 MeV. A region of inhomogeneous instability indicated by a negative wave function renormalization is found withμB≳ 420 MeV. It is found that the non-monotonic dependence of the kurtosis of the net-proton number distributions on the beam collision energy observed in experiments could arise from the increasingly sharp crossover in the regime of low collision energy.
A random energy approach to deep learning
Authors: Xie Rongrong , Marsili Matteo
Published: August 2022

We study a generic ensemble of deep belief networks (DBN) which is parametrized by the distribution of energy levels of the hidden states of each layer. We show that, within a random energy approach, statistical dependence can propagate from the visible to deep layers only if each layer is tuned close to the critical point during learning. As a consequence, efficiently trained learning machines are characterised by a broad distribution of energy levels. The analysis of DBNs and restricted Boltzmann machines on different datasets confirms these conclusions.
Exactly solvable model of a passive Brownian heat engine and its comparison with active engines
Authors: Majumdar Rita , Saha Arnab , Marathe Rahul
Published: August 2022

We perform an extensive analysis of passive as well as active micro-heat engines with different single-particle stochastic models. Using stochastic thermodynamics we calculate the thermodynamic work, heat, entropy production and efficiency of passive and active Brownian heat engines analytically, as well as numerically, and compare them. We run the heat engines with a protocol for which the average thermodynamic quantities are calculated exactly for an arbitrary cycle time. We also discuss the group of protocols for which exact non-quasistatic calculations can be done, completely in the passive engine case and partially in the active engines. We obtain detailed thermodynamics of non-quasistatic (i.e. powerful) single-particle micro heat engines. The quasistatic (i.e. zero power) limit of the results is obtained by taking a long (infinite) cycle time. We also study the distributions of position of the confined particle in both passive and active engines. We compare their characteristics in terms of the parameter that measures the competition between the active persistence in the particle position (due to active noises) and the harmonic confinement. We also calculate excess kurtosis that measures the non-Gaussianity of these distributions. Our analysis shows that the efficiency of such thermal machines can be enhanced or reduced depending on the activity present in the model.
Ship Navigation and Fuel Profiling based on Noon Report using Neural Network Generative Modeling
Authors: Hadi J , Tay Z Y , Konovessis D
Published: August 2022

Harbor craft historical routes contain valuable information on how the experienced crews navigate around the known waters while performing jobs. The noon report logs each job timeframe which can be used to segregate the time-series positional data as routes. Other information from the noon report such as fuel consumption could be associated with a particular job as well. This paper offers a solution to encompass crew navigational experience into neural network models. The variational autoencoder, which is a generative model, can capture the routes into a knowledge base model. The same variational autoencoder is also able to train other neural networks to make predictions of route and fuel consumption based on job metadata (I.e., job duration, activity area, and route classification). The predicted routes could be used as a cost map for pathfinding algorithms such as A* or Dijkstra.
Ship-Shore Interaction: The Model in the Middle
Authors: Hagaseth Marianne , Juhl Jeppe Skovbakke , Rødseth Ørnulf Jan , Scherpenzeel Ben van , Wurff Andreas Maria van der
Published: August 2022

The complex picture of maritime transport involving more than 100 thousand ships, more than 8000 ports and a large number of stakeholders fulfilling different roles and being responsible for different processes means that providing up-to-date and timely information during port calls is a complex task. In addition, there are requirements to reduce both the environmental footprint and costs of the maritime transport. From 2019, the International Maritime Organization (IMO) made it mandatory to accept electronic clearance of ships entering foreign ports, meaning that the digitalization of ship-port interfaces to support the port call processes has become an important topic. Further, this means that the interoperability between a large number of ICT systems to support the end-users related to a port call, must be ensured. This paper describes the model in the middle, by which we mean a "least common multiple" regarding data elements and data models to support a consistent exchange of information between preferably all involved stakeholders during a port call.
Concept design of a digital twin architecture for ship structural health management
Authors: Cheng Zhiping , Tan Eric , Cai Minbo , Magee Allan Ross
Published: August 2022

Ocean-going vessels frequently experience severe weather conditions. Occasionally, the actual environmental loads are much larger than design values, resulting in deviations from design conditions that may cause serious structural damage. A structural digital twin can enhance predictability and reliability of marine structures, and thus provide vessel operators, owners, and stakeholders with a more accurate overview of a vessel’s condition. It can also help reduce lifecycle costs through proposing rational and optimal inspection, maintenance, repair programs, and assist on maximizing service life and mission availability. This paper uses a benchmark vessel to investigate structural behaviors of the vessel through dynamic loading approach. The correlation between structure members and critical responses are established, and high stress concentration areas have been identified. Subsequently, this paper develops a conceptual digital twin architecture. The proposed digital twin predicts responses of the entire structure to measured or predicted environmental conditions with a hybrid model combining numerical simulations with measurements. While the traditional structural monitoring system focuses on the health condition of typical hot spots, the proposed digital twin may improve structural health awareness of the entire hull structure based on a limited number of sensors.
Objective and intelligent training assessment package for maritime training in simulator
Authors: Sam O , Le D , Ang G A , Liu Y , Zhang D
Published: August 2022

Training in simulator has been used in maritime domain for years due to its cost-effective nature. Different scenarios with varied visibility, traffic density, weather conditions, etc. could be easily set up in the simulators. However, the existing build-in training and assessment package in the simulators is rigid as it does not take into consideration the change in traffic and navigational environment. Human experts are always involved to observe and assess the performance of trainees. An objective and intelligent training and assessment package is proposed to assist the experts in training to ensure objectivity and consistency. To identify the gaps and determine the relevance and the adequacy of the existing build-in assessment in the simulator, online survey has been distributed to the shipping companies and associations. The survey has gathered inputs on the actual shipboard practices when the seafarers are navigating in Singapore waters. This includes different types of vessels, vessel sizes, and external environment conditions such as visibility. The outcome of this analysis is used to form the baseline of a common practice at sea and used in the training and assessment package, which provides consistency in setting the critical training parameters. The training and assessment package reads the data from an advanced navigation research simulator and is able to sense changes and update itself in accordance with user-defined environment. Several assessment modules such as CPA under different traffic density and visibility, minimum distance from other vessels, rate of turn at different speed and loading conditions, will be covered by this training and assessment package.
Model-Based Design and Safety Assessment for Crewless Autonomous Vessel
Authors: Nakashima Takuya , Kutsuna Koji , Kureta Rui , Nishiyama Hisaki , Yanagihara Tomoya , Nakamura Jun , Ando Hideyuki , Murayama Hideaki , Kuwahara Satoru
Published: August 2022

The Designing the Future of Full Autonomous Ship (DFFAS) Project conducted the crewless maritime autonomous surface ship long-distance demonstration in congested waters in March 2022. This study shows a model-based systematic design methodology and a safety evaluation method for autonomous ships conducted through this project. A reference model of ConOps (Concept of Operations) for autonomous navigation systems is proposed using the DFFAS system as an example. System Theoretic Process Analysis (STPA) is also applied at the subsystem and component levels according to the actual system development phase to extract appropriate granularity of safety requirements.
Development of Recommendations for Digital Testing of MASS Navigation Safety prior to Sea Trials
Authors: Chua Kie Hian , Coutinho Savio , Norahim Aizad , Konovessis Dimitrios
Published: August 2022

For Maritime Autonomous Surface Ships (MASS), a key area that has seen active development is in the use of autonomous capabilities for vessel navigation and control. This can range from a simple use case of waypoint navigation, which takes into account bathymetry and navigation markers, to complex collision avoidance scenarios where the autonomous systems are required to detect, evaluate and execute evasive manoeuvres based on time and spatially varying dynamic behaviour of other vessels. In Singapore, it has been identified that there is a need to carry out accurate digital testing of MASS navigation safety before sea trials. This is where a vessel developer is required to demonstrate that the MASS is able to carry out the sea trials safely, and to stress test high risk scenarios that may not be practicably tested in the sea trials. A study has been carried out to develop recommendations for the digital testing, which takes into consideration the need for accurate representation of the actual MASS being built, as well as the verification of the autonomous navigation algorithm’s capabilities to safely control the vessel in real-world scenarios. Based on the study, a three-stage framework is proposed. Firstly, the accuracy of the digital model in representing the dynamic responses of the actual vessel is verified and any discrepancy with benchmark data is to be quantified. Secondly, tests are carried out to ascertain that the autonomous navigation algorithm is able to control (virtually) the dynamically-accurate vessel from one point to another, taking into account the real-world environmental loads. Lastly, the ability of the autonomous navigation algorithm in carrying out collision detection and avoidance is verified. As part of the study, a review of the current state-of-art and engagement with the industry has been carried out. These details are described in this paper.
Ship route optimization using hybrid physics-guided machine learning
Authors: Jørgensen Ulrik , Belingmo Pauline Røstum , Murray Brian , Berge Svein Peder , Pobitzer Armin
Published: August 2022

This paper presents a method for energy efficient weather routing of a ferry in Norway. Historical operational data from the ferry and environmental data are used to develop two models that predict the energy consumption. The first is a purely data-driven linear regression energy model, while the second is as a hybrid model, combining physical models with data-driven models using machine learning techniques. With an established energy model, it is possible to develop a route optimization that proposes efficient routes with less energy usage compared to fixed speed and heading control.
Development of Monte Carlo based treatment planning system for BNCT
Authors: Chen Jiang , Teng Yi-Chiao , Zhong Wan-Bing , Yang Hai-Bo , Hong Qing , Liu Yuan-Hao
Published: August 2022

A treatment planning system (TPS) plays a major role for a successful radiotherapy, directly influencing the calculated dose accuracy, and thus the treatment quality. Multifunctional Arithmetic for Neutron Transportation Analysis (NeuMANTA), a TPS especially designed for complete workflow for BNCT, which aims to provide high precision dose calculation with maximizing the efficacy. The dedicated MC engine COMPASS seamlessly embedded in NeuMANTA can be called for dose distribution calculation in background. Optimized cross-section library, parallel computing, and various variance reduction techniques are applied to speed up the particle transportations. A benchmark was performed between NeuMANTA and MCNP6, and results agreed well with no significant statistical difference, however, NeuMANTA needs only half of the calculation time. The accuracy of estimated doses, and complete treatment workflow are the main features in NeuMANTA.
Synchronization time in two coupled cluster networks based on discontinuous map
Authors: Yang Yunfeng , Bai Xue
Published: August 2022

The synchronization time in the coupled discontinuous maps is investigated. The results show that the synchronization time of the coupled discontinuous systems exhibits a non-monotonic behaviour as the coupling strength increases. Moreover, a coexistence attractor, which consists of a period state and synchronization one, is found, and it exhibits a riddle basin character. The initial conditions of coupled systems, which is close to the basin boundary of period attractor, can lead to a long quasiperiodic transient, and the trajectory jumps from one region to another one in the phase space. Finally, the non-monotonic behaviour of the synchronization time of the coupled discontinuous systems is also checked in other types of discontinuous maps.
A novel voltage protection method for multi-cell lithium-ion battery protection IC
Authors: Chen Zhijian , Wu Xinyi , Li Bin , Lin Xiaoling , Xiao Rui , Feng Guangyin , Wang Yanjie
Published: August 2022

Lithium batteries have been widely used in portable electronic devices and other electric products. To ensure safety and long life, a lithium battery needs to be equipped with a protection chip. A novel voltage protection method for three-cell lithium-ion battery protection IC (Integrated Circuit) is proposed in this paper. A new voltage protection circuit structure and a three-cell lithium battery voltage sampling circuit are presented to improve the circuit performance of the chip and reduce the dynamic power consumption and chip area of the system. With a new time-division multiplexing circuit structure, the area and power consumption of the chip are greatly reduced. Moreover, this solution can be extended to any number of lithium battery packs connected in series for voltage protection. Testing results show that the overcharge detection accuracy can achieve better than ±15mV, the over-discharge detection accuracy can achieve ±7.5mV, the power consumption of the voltage protection module is 1.7μA, and the area is 300μm×500μm2.
Cascade integration of nonlinear phenomena exhibited by monometallic nanoparticles
Authors: Estrada-León Soledad D.
Published: August 2022

In this work were numerically analyzed the third-order nonlinear optical effects exhibited by combinations of uncoupled monometallic silver, gold and platinum nanoparticles. The nanosystems were considered to be homogeneous and surrounded by a dielectric matrix. The design of the nanostructures was evaluated as a collective behavior resulting from the specific order of the set in trilayer tandem form. The characteristic Localized Surface Plasmon Resonance phenomena in the yellow, green and ultraviolet absorption bands for the Ag, Au and Pt; respectively, were considered. Different permutations of the three kind of monometallic elements selected in sequence were studied by using the wave equation and the finite difference method. Immediate indications useful for exploring nonlinear nanodevices and for building up nanostructured platforms based on nanoscale functions can be anticipated from this work.
Simulation system of lighting environment for optical imaging test
Authors: Zhang Lei , Yang Yu , Zhao Shuai , Xu Wenbin , Cai Bolin , Wang Keyi
Published: August 2022

In order to overcome the shortcomings of the solar simulator in the aspect of the performance testing for optical imaging system, a lighting environment simulation system is designed. We select dysprosium lamp, xenon lamp and multiple LEDs as light sources of the solar simulator, and the change of the sun zenith angle is simulated by using the symmetrical method of the light source. Also, the light intensity is controlled by adjusting the output current of the power supply. Lighting environment simulation system not only can simulate spectral irradiance and intensity change of real solar, but also can simulate the real sun depending on the season and the angle of illumination period. This system provided a technical support for the performance testing of optical imaging systems.
Oscillating charge currents of one-dimensional Hubbard model in electric field
Authors: Zheng Yong
Published: August 2022

The time evolution properties of charge current for the one-dimensional Hubbard model in an electric field have been studied in a rigorous manner. We find that there is a complete and orthonormal set of time-evolution states for which the charge current can only keep zero or oscillate constantly, differing from the possible picture of damped or over-damped Bloch oscillations due to strong correlations. It is also found that, associated with these states, there is a set of constant phase factors, which are uniquely determined and are very useful on discussing the long-time evolution behaviors of the system.
Analysis of discharge characteristics of pulsed plasma power source in the microsecond scale
Authors: Zhang Qian , Liu Zhiheng , Lin Deling , Hu Yuzhe , Zheng Borui , Zhao Taifei
Published: August 2022

The characteristics test of plasma discharge is an essential physical basis for studying plasma flow control. The power consumption of pulsed plasma aerodynamic actuation is 30% lower than when the actuation voltage is a continuous sine wave. This paper uses a self-developed pulsed plasma power source to superimpose DC. The power source conducts the discharge measurement on the sliding discharge plasma. The experimental results show that the power source effectively outputs 0-20 kV pulsed high voltage. The superimposed DC power source generates a negative DC high voltage, accelerating the drift speed of positive ions in the plasma and forming a stable and uniform surface discharge. But the essence of pulse discharge is still filamentary discharge. In a cycle, the plasma discharge is mainly concentrated on the rising edge of the pulse. In contrast, the pulse current is bipolar, and the negative pulse current has a more obvious growth trend, which is more effective for improving the flow control ability.
Numerical analysis and optimization of radio-frequency ion trap potential
Authors: Liu Yuhan , Du Lijun , He Yuling , Huang Shiyi , Zhang Qiang , He Keliang , Tang Yulong , Meng Yansong , Zhai Shenghua
Published: August 2022

The trap of multi-ion frequency standard is an ideal candidate for a new generation of ground and space-borne timekeeping systems, which has high signal-to-noise ratio, low frequency drift rate and excellent long-term frequency stability. The non-ideal characteristic of radio-frequency potential is one of the dominant factors that restrict the performance of ion frequency standard. In this study, the finite element numerical analysis method is used to quantitatively analyse and optimize the electrical potential field of ion trap, and an analytical model of ideal trapping potential is established. The typical transient numerical potential surface of trapping potential is used for decoupling analysis of various electrical potential effects. Based on the optimal structure parameters, the numerical model and analytical model of non-standard ion trap are established to verify the validity and accuracy of the numerical analysis method. This method can provide a quantitative solution for the high precision reconstruction of the trapping potential model of heterotype ion traps.
Bacteria-inspired magnetically actuated rod-like soft robot in viscous fluids
Authors: Bhattacharjee Anuruddha , Jabbarzadeh Mehdi , Kararsiz Gokhan , Fu Henry C , Kim Min Jun
Published: August 2022

This paper seeks to design, develop, and explore the locomotive dynamics and morphological adaptability of a bacteria-inspired rod-like soft robot propelled in highly viscous Newtonian fluids. The soft robots were fabricated as tapered, hollow rod-like soft scaffolds by applying a robust and economic molding technique to a polyacrylamide-based hydrogel polymer. Cylindrical micro-magnets were embedded in both ends of the soft scaffolds, which allowed bending (deformation) and actuation under a uniform rotating magnetic field. We demonstrated that the tapered rod-like soft robot in viscous Newtonian fluids could perform two types of propulsion; boundary rolling was displayed when the soft robot was located near a boundary, and swimming was displayed far away from the boundary. In addition, we performed numerical simulations to understand the swimming propulsion along the rotating axis and the way in which this propulsion is affected by the soft robot’s design, rotation frequency, and fluid viscosity. Our results suggest that a simple geometrical asymmetry enables the rod-like soft robot to perform propulsion in the low Reynolds number (Re ≪ 1) regime; these promising results provide essential insights into the improvements that must be made to integrate the soft robots into minimally invasive in vivo applications.
Get a grip: inward dactyl motions improve efficiency of sideways-walking gait for an amphibious crab-like robot
Authors: Graf N M , Grezmak J E , Daltorio K A
Published: August 2022

Crabs are adept at traversing natural terrains that are challenging for mobile robots. Curved dactyls are a characteristic feature that engage terrain in order to resist wave forces in surf zones. Inward gripping motions at the onset of the stance could increase stability. Here, we add inward gripping motions to the foot trajectories of walking gaits to determine the energetic costs and speed for our 12 degree of freedom (DOF) crab-like robot, Sebastian. Specifically, we compared two gaits in which the step size (stance length) was the same, but the swing trajectories were either triangular (to minimize trajectory length) or quadrilateral (in which the leg deliberately oversteps in order to perform a distributed inward grip). The resulting gripping quadrilateral gait significantly outperformed the nongripping triangular gait on diverse terrains (hard linoleum, soft mats, and underwater sand), providing between 15% and 34% energy savings. Using this gait eliminates the advantage of spherical end effectors for slip reduction on hard linoleum, which may lead to a better understanding of how to use crab-like morphology for more efficient locomotion. Finally, we subjected the walking robot to lab-generated waves with a wave height approximately 166% of the dactyl length. Both gaits enabled the robot to walk undisturbed by the waves. Taken together, these results suggest that impact trajectory will be key for future amphibious robots. Future work can provide a deeper understanding of the relationships between dactyls, gaits, and substrates in biology and robots.
A bioinspired robotic knee with controlled joint surfaces and adjustable ligaments
Authors: Liang Wei , Wu Wei , Chen Wei , Ren Lei , Wang Kunyang , Qian Zhihui , Ren Luquan
Published: August 2022

The knee joint plays a key role in kinematic and kinetic performances of pedestrain locomotion. The key role of meniscus with matched ligaments in joint stability and movability has not been fully explored in current robotic knee designs. We fabricate a bioinspired robotic knee based on a kinematic model of an anatomical knee in order to reveal the relationship between the meniscus, ligaments and their stability and movability, respectively. The kinematic model was built from magnetic resonance imaging of the human knee with generated contact profiles and customized ligament fibers. Then, the bioinspired knee was designed, and its dynamic stability was maintained by ligaments and specific contact profiles, which were acquired based on the kinematic model. Finally, a monopod robot with the bioinspired knee assembled was developed for dynamic testing. The results show that (1) a smooth rolling–sliding motion can be achieved with the addition of menisci and compatible ligaments; and (2) joint stiffness can be adjusted by changing the springs and activation lengths of ligament fibers. This study gives biomimetic insights into a new design of knee joint for a robotic/prosthetic leg.
The SAGEX review on scattering amplitudes Chapter 7: Positive geometry of scattering amplitudes
Authors: Herrmann Enrico , Trnka Jaroslav
Published: August 2022

Scattering amplitudes are both a wonderful playground to discover novel ideas in quantum field theory and simultaneously of immense phenomenological importance to make precision predictions for e.g. particle collider observables and more recently also for gravitational wave signals. In this review chapter, we give an overview of some of the exciting recent progress on reformulating QFT in terms of mathematical, geometric quantities, such as polytopes, associahedra, Grassmanians, and the amplituhedron. In this novel approach, standard notions of locality and unitarity are derived concepts rather than fundamental ingredients in the construction which might give us a handle on a number of open questions in QFT that have evaded an answer for decades. We first give a basic summary of positive geometry before discussing the associahedron—one of the simplest physically relevant geometric examples—and its relation to tree-level scattering amplitudes in bi-adjoint ϕ
3 theory. Our second example is the amplituhedron construction for scattering amplitudes in planar maximally supersymmetric Yang–Mills theory.
A superconducting nanowire-based architecture for neuromorphic computing
Authors: Lombo Andres E , Lares Jesus , Castellani Matteo , Chou Chi-Ning , Lynch Nancy , Berggren Karl K
Published: August 2022

Neuromorphic computing would benefit from the utilization of improved customized hardware. However, the translation of neuromorphic algorithms to hardware is not easily accomplished. In particular, building superconducting neuromorphic systems requires expertise in both superconducting physics and theoretical neuroscience, which makes such design particularly challenging. In this work, we aim to bridge this gap by presenting a tool and methodology to translate algorithmic parameters into circuit specifications. We first show the correspondence between theoretical neuroscience models and the dynamics of our circuit topologies. We then apply this tool to solve a linear system and implement Boolean logic gates by creating spiking neural networks with our superconducting nanowire-based hardware.
Causal and Associational Language in Observational Health Research: A Systematic Evaluation
Authors: Haber Noah A , Wieten Sarah E , Rohrer Julia M , Arah Onyebuchi A , Tennant Peter W G , Stuart Elizabeth A , Murray Eleanor J , Pilleron Sophie , Lam Sze Tung , Riederer Emily , Howcutt Sarah Jane , Simmons Alison E , Leyrat Clémence , Schoenegger Philipp , Booman Anna , Dufour Mi-Suk Kang , O’Donoghue Ashley L , Baglini Rebekah , Do Stefanie , Takashima Mari De La Rosa , Evans Thomas Rhys , Rodriguez-Molina Daloha , Alsalti Taym M , Dunleavy Daniel J , Meyerowitz-Katz Gideon , Antonietti Alberto , Calvache Jose A , Kelson Mark J , Salvia Meg G , Parra Camila Olarte , Khalatbari-Soltani Saman , McLinden Taylor , Chatton Arthur , Seiler Jessie , Steriu Andreea , Alshihayb Talal S , Twardowski Sarah E , Dabravolskaj Julia , Au Eric , Hoopsick Rachel A , Suresh Shashank , Judd Nicholas , Peña Sebastián , Axfors Cathrine , Khan Palwasha , Rivera Aguirre Ariadne E , Odo Nnaemeka U , Schmid Ian , Fox Matthew P
Published: August 2022

We estimated the degree to which language used in the high-profile medical/public health/epidemiology literature implied causality using language linking exposures to outcomes and action recommendations; examined disconnects between language and recommendations; identified the most common linking phrases; and estimated how strongly linking phrases imply causality. We searched for and screened 1,170 articles from 18 high-profile journals (65 per journal) published from 2010–2019. Based on written framing and systematic guidance, 3 reviewers rated the degree of causality implied in abstracts and full text for exposure/outcome linking language and action recommendations. Reviewers rated the causal implication of exposure/outcome linking language as none (no causal implication) in 13.8%, weak in 34.2%, moderate in 33.2%, and strong in 18.7% of abstracts. The implied causality of action recommendations was higher than the implied causality of linking sentences for 44.5% or commensurate for 40.3% of articles. The most common linking word in abstracts was “associate” (45.7%). Reviewers’ ratings of linking word roots were highly heterogeneous; over half of reviewers rated “association” as having at least some causal implication. This research undercuts the assumption that avoiding “causal” words leads to clarity of interpretation in medical research.
Assessing the Fit of N95 Filtering Facepiece Respirators Fitted with an Ear Loop Strap System: A Pilot Study
Authors: Niu Xinyi , Koehler Richard H , Yermakov Michael , Grinshpun Sergey A
Published: August 2022

Throughout the COVID-19 pandemic, hundreds of millions of people worldwide have become new users of respiratory protective devices. Facemasks and KN95 respirators utilizing an ear loop straps system (ELSS) have recently become popular among occupational and non-occupational populations. Part of this popularity is due to the ease of wearability as compared with traditional devices utilizing two headbands, one worn over the head and the other behind the neck—a universal strap system used in NIOSH-certified N95 filtering facepiece respirators (FFRs). Some users convert the two-strap configuration to an adjustable ELSS. The first objective of this pilot study was to quantitatively characterize how such a conversion impacts the respirator fit. Additionally, a novel faceseal (NFS) technology, which has been previously demonstrated to enhance the fit of N95 FFRs, was deployed to modify the ELSS-converted N95 FFRs. The second objective of this study was to quantify the fit improvement that results from adding the NFS to the ELSS. The study was conducted by performing the Occupational Safety and Health Administration (OSHA)-approved quantitative fit testing (QNFT) on 16 human subjects featuring different facial shapes and dimensions. Three models of cup-shaped N95 FFRs were tested in three versions: the standard version with manufacturer’s strap system, the ELSS-converted, and the ELSS-converted version modified by adding the NFS. QNFT demonstrated that the fit of an N95 FFR featuring the traditional/standard headbands strap system is negatively impacted when this system is converted to an ELSS. The fit of an ELSS-converted respirator can be significantly improved by the addition of the NFS. We found that the FFR model and the strap system version are significant factors affecting the QNFT-determined respirator fit factor (FF), as well as the OSHA QNFT pass rate (FF ≥100). The findings suggest that the current NFS, if further improved, has a potential for developing a ‘universally fitting’ ELSS-equipped N95 FFR that can be used by the general public, the vast majority of whom do not have access to OSHA fit requirements.
Call combinations in chimpanzees: a social tool?
Authors: Leroux Maël , Chandia Bosco , Bosshard Alexandra B , Zuberbühler Klaus , Townsend Simon W
Published: August 2022

A growing body of evidence suggests the capacity for animals to combine calls into larger communicative structures is more common than previously assumed. Despite its cross-taxa prevalence, little is known regarding the evolutionary pressures driving such combinatorial abilities. One dominant hypothesis posits that social complexity and vocal complexity are linked, with changes in social structuring (e.g., group size) driving the emergence of ever-more complex vocal abilities, such as call sequencing. In this paper, we tested this hypothesis through investigating combinatoriality in the vocal system of the highly social chimpanzee. Specifically, we predicted combinatoriality to be more common in socially-driven contexts and in females and lower-ranked males (socially challenging contexts and socially challenged individuals respectively). Firstly, through applying methods from computational linguistics (i.e., collocation analyses), we built an objective repertoire of combinatorial structures in this species. Second, we investigated what potential factors influenced call combination production. We show that combinatoriality is predominant in 1) social contexts vs. non-social contexts, 2) females vs. males, and 3) negatively correlates with male rank. Together, these results suggest one function of combinatoriality in chimpanzees may be to help individuals navigate their dynamic social world. More generally, we argue these findings provide support for the hypothesized link between social and vocal complexity and can provide insight into the evolution of our own highly combinatorial communication system, language.
A novel method for handling pre-existing conditions in multivariate prediction model development for COVID-19 death in the Department of Veterans Affairs
Authors: Campbell Heather M , Murata Allison E , Mao Jenny T , McMahon Benjamin , Murata Glen H
Published: August 2022

Many mathematical models have been proposed to predict death following the Coronavirus Disease 2019 (COVID-19); all started with comorbidity subsets for this still-little understood disease. Thus, we derived a novel predicted probability of death model (PDeathDx) upon all diagnostic codes documented in the Department of Veterans Affairs. We present the conceptual underpinnings and analytic approach in estimating the independent contribution of pre-existing conditions. This is the largest study to-date following patients with COVID-19 to predict mortality. Cases were identified with at least one positive nucleic acid amplification test. Starting in 1997, we use diagnoses from the first time a patient sought care until 14 days before a positive nucleic acid amplification test. We demonstrate the clear advantage of using an unrestricted set of pre-existing conditions to model COVID-19 mortality, as models using conventional comorbidity indices often assign little weight or usually do not include some of the highest risk conditions; the same is true of conditions associated with COVID-19 severity. Our findings suggest that it is risky to pick comorbidities for analysis without a systematic review of all those experienced by the cohort. Unlike conventional approaches, our comprehensive methodology provides the flexibility that has been advocated for comorbidity indices since 1993; such an approach can be readily adapted for other diseases and outcomes. With our comorbidity risk adjustment approach outperforming conventional indices for predicting COVID-19 mortality, it shows promise for predicting outcomes for other conditions of interest.
miR-3168 promotes hepatocellular carcinoma progression via downregulating p53
Authors: Lu Tingting , Han Tao , Zhao Mingfang
Published: August 2022

Hepatocellular carcinoma (HCC) is a highly malignant disease with poor prognosis, which is partly due to the presence of liver cancer stem cells (CSCs). CSCs participate in tumor recurrence, metastasis, and chemoresistance. However, the mechanisms underlying liver CSC regulation are unknown. In this study, we found that miR-3168 expression is increased in HCC and that it predicts poor prognosis. Functional assays showed that miR-3168 promotes HCC cells’ proliferation and facilitates liver CSC self-renewal and tumorigenicity. Mechanistically, bioinformatics and the luciferase reporter assay demonstrated that miR-3168 targets the 3'UTR of the p53 mRNA. MiR-3168 expression was negatively correlated with p53 mRNA in HCC tissue samples. Rescue assays demonstrated that p53 knockdown abrogates the discrepancies in proliferation, self-renewal, and tumorigenicity between miR-3168 knockdown HCC cells and control HCC cells. Furthermore, miR-3168 expression was negatively correlated with p53 in HCC tissues. The combined HCC panels exhibited a worse prognostic value for HCC patients than any of these components alone. Moreover, miR-3168 expression was increased in cisplatin-resistant HCC cells and patient-derived xenografts. Clinical cohort analysis revealed that HCC patients with low miR-3168 levels have a superior survival rate when treated with postoperative transcatheter arterial chemoembolization compared with that of patients with high miR-3168 levels. In conclusion, our study uncovered a novel mechanism of liver CSC regulation and provided a potential therapeutic target for liver CSCs.