Relevant Modes Research Articles

Rule 54: exactly solvable model of nonequilibrium statistical mechanics

We review recent results on an exactly solvable model of nonequilibrium statistical mechanics, specifically the classical rule 54 reversible cellular automaton and some of its quantum extensions. We discuss the exact microscopic description of nonequilibrium dynamics as well as the equilibrium and nonequilibrium stationary states. This allows us to obtain a rigorous handle on the corresponding emergent hydrodynamic description, which is treated as well. Specifically, we focus on two different paradigms of rule 54 dynamics. Firstly, we consider a finite chain driven by stochastic boundaries, where we provide exact matrix product descriptions of the nonequilibrium steady state, most relevant decay modes, as well as the eigenvector of the tilted Markov chain yielding exact large deviations for a broad class of local and extensive observables. Secondly, we treat the explicit dynamics of macro-states on an infinite lattice and discuss exact closed form results for dynamical structure factor, multi-time-correlation functions and inhomogeneous quenches. Remarkably, these results prove that the model, despite its simplicity, behaves like a regular fluid with coexistence of ballistic (sound) and diffusive (heat) transport. Finally, we briefly discuss quantum interpretation of rule 54 dynamics and explicit results on dynamical spreading of local operators and operator entanglement.

Quantifying clinical severity of physics errors in high-dose rate prostate brachytherapy using simulations

PURPOSETo quantitatively evaluate through automated simulations the clinical significance of potential high-dose rate (HDR) prostate brachytherapy (HDRPB) physics errors selected from our internal failure-modes and effect analysis (FMEA). METHODS AND MATERIALSA list of failure modes was compiled and scored independently by 8 brachytherapy physicists on a one-to-ten scale for severity (S), occurrence (O), and detectability (D), with risk priority number (RPN) = SxOxD. Variability of RPNs across observers (standard deviation/average) was calculated. Six idealized HDRPB plans were generated, and error simulations were performed: single (N = 1722) and systematic (N = 126) catheter shifts (craniocaudal; -1cm:1 cm); single catheter digitization errors (tip and connector needle-tips displaced independently in random directions; 0.1 cm:0.5 cm; N = 44,318); and swaps (two catheters swapped during digitization or connection; N = 528). The deviations due to each error in prostate D90%, urethra D20%, and rectum D1cm3 were analyzed using two thresholds: 5–20% (possible clinical impact) and >20% (potentially reportable events). RESULTSTwenty-nine relevant failure modes were described. Overall, RPNs ranged from 6 to 108 (average ± 1 standard deviation, 46 ± 23), with responder variability ranging from 19% to 184% (average 75% ± 30%). Potentially reportable events were observed in the simulations for systematic shifts >0.4 cm for prostate and digitization errors >0.3 cm for the urethra and >0.4 cm for rectum. Possible clinical impact was observed for catheter swaps (all organs), systematic shifts >0.2 cm for prostate and >0.4 cm for rectum, and digitization errors >0.2 cm for prostate and >0.1 cm for urethra and rectum. CONCLUSIONSA high variability in RPN scores was observed. Systematic simulations can provide insight in the severity scoring of multiple failure modes, supplementing typical FMEA approaches.

Parametric non-intrusive model order reduction for flow-fields using unsupervised machine learning

An improved data-driven non-intrusive model order reduction (MOR) methodology capable of interpolating time-transient flow-fields and other types of data with respect to the parameters is proposed. The proposed MOR method comprises the following two stages: MOR and interpolation. For the MOR, modified proper orthogonal decomposition (POD) is used to collect the parametrically independent POD modes and dependent coefficients. An interpolation of the POD coefficients is conducted through unsupervised machine learning, referred to as the Wasserstein generative adversarial network-gradient penalty (WGAN-GP). By using a deep convolutional neural network, WGAN-GP stabilizes the interpolation across the parameters and ensures an accurate interpolation with few results within the parametric space. An interpolated object is then generated using the parametrically interpolated POD coefficients and relevant independent modes. Next, flow-fields around a stationary cylinder and a plunging airfoil are applied to demonstrate the efficiency and accuracy of the proposed approach, and the influences of the POD modes and parameters on the accuracy are evaluated. Finally, the accuracy and efficiency are compared with those of other methods through the adoption of an accuracy index. Based on the results, the proposed method was found to be effective and efficient for object interpolation.

Composition Optimization of Triple Conducting PrNixCo1-XO3-δ Oxygen Electrodes for Protonic Ceramic Electrochemical Cells

Using protonic ceramic electrochemical cells (PCECs) to produce hydrogen is a promising approach to achieve the renewable energy storage, and development of critical materials is the key step to facilitate fast hydrogen production rate. Particularly, the sluggish electrode kinetic at reduced temperatures (400~600 °C) and chemical stability under realistic high steam concentration raises concern. We have recently reported a triple conducting oxide of PrNi0.5Co0.5O3-δ perovskite as an oxygen electrode in PCECs, which exhibits superior electrochemical performance in both fuel cell and electrolysis modes, and potential increased stability due to the absence of alkaline elements such as Ba and Sr in the composition. In this work, the continuous composition optimization of PrNixCo1-xO3-δ (x=0.1, 0.3, 0.5, 0.7, and 0.9) oxides is carried out to find the dependence of Ni/Co ratio on the catalytic activity towards oxygen reduction and water splitting reactions. The isotope water temperature-programmed desorption and thermogravimetric analysis is used to study the water uptake capability for understanding the proton concentration variation as function of doping level. The Fourier-transform infrared spectroscopy (FTIR) is also utilized to observe relative intensity change of the hydroxyl band on electrode surface to further explain the possible species evolution in the relevant reaction modes. This work provides a representative approach on composition optimization for oxygen electrode candidate down selection.

Modalities of renal replacement therapy and clinical outcomes of patients with acute kidney injury in a resource-limited setting: Results from a SEA-AKI study.

To determine the effects of modalities of renal replacement therapy (RRT) on the 30-d mortality and renal recovery in patients with acute kidney injury (AKI). A multicenter cohort study was conducted in 17 hospitals from Thailand and Indonesia. We recruited patients who were admitted to the Intensive care unit and diagnosed with AKI. Relevant mode of RRT, as intermittent hemodialysis (IHD), continuous renal replacement therapy (CRRT), peritoneal dialysis (PD), or sustained low efficiency dialysis (SLED), was initiated as indicated. From 2844 patients with AKI, 449 cases (8.1%) received RRT. There were no significant differences in the 30-d mortality between those initially treated with CRRT, PD, and SLED compared to those treated with IHD. The renal recovery was similar for each RRT mode. The three independent factors of death were the primary diagnosis of kidney disease, higher APACHE II score, and non-renal SOFA score. Only 48 (10.7%) patients had been switched to another mode of RRT. All four modes of RRT (IHD, CRRT, PD, and SLED) are acceptable treatments for severe AKI and gave a similar survival rate.

The role of schools as an opportunity for transmission of local knowledge about useful Restinga plants: experiences in southeastern Brazil

BackgroundThe study of cultural transmission can help identify processes that influence knowledge systems dynamics and evolution, especially during childhood and youth, which are fundamental phases in acquiring survival skills. In this sense, we use the knowledge about useful restinga plants (Brazilian coastal vegetation) as an analytical model to describe, compare, and analyze cultural transmission during youth, while factoring in origin, in the Cabo Frio region, southeastern Brazil. We tested (1) whether transmission of knowledge is conservative, (2) whether immigration events define the transmission modes, (3) whether teaching is the most important social transmission cognitive process, and (4) which type of stimulus/context is most important for the knowledge transmission process.MethodsQuestionnaires and free listings were applied to 150 high school students aged between 15 and 20 to obtain information about socioeconomic characteristics, useful plant knowledge, and cultural transmission. We analyzed the distribution of knowledge according to the informant’s origin and evaluated the models, processes, and context with which this information was transmitted. The chi-square test was used to determine the association between origin, plant knowledge, and transmission as well as to reveal the most important models, modes, and processes during youth.ResultsInformants provided 299 plant citations ( overline{x} = 1.75; s = 1.73) related to 37 species. The categories of the most cited uses were edible (93) and medicinal (32). Statistical results showed that origin did not influence knowledge distribution and transmission. In addition, although the most relevant mode was the conservative (vertical) one, the one-to-many diffuse mode (teacher) was highlighted. The new environmental context for immigrants did not influence transmission, the main transmission process was teaching, and the learning contexts were predominantly school-related.ConclusionPlant knowledge in youth was related to local edible and medicinal plants, indicating adaptive knowledge linked to material demands for survival. While the initial models for cultural transmission are family (vertical), during the development phase of juveniles, other actors become models (one-to-many). In addition, the nature of the information (survival demand) and age are more relevant to cultural transmission than the socio-environmental context.

A novel energy losses dependence on integral swirl flow parameters in an elbow draft tube of a Kaplan turbine

Energy losses in the region between the runner and outlet section of a conventional hydraulic turbine have been the subject of investigation for a long time. In this paper as well, elbow draft tube losses are determined for the relevant wide range on-cam operating modes of the Kaplan turbine using a contemporary approach. The research considers the impact of swirl flow parameters, defined for the referent inlet of the draft tube, on the hydraulic losses. According to the methodology and obtained numerical results, a new formula for the calculation of draft tube losses is proposed. In the process of a hydropower plant refurbishment, the presented approach may enable more efficient and economically justified consideration of the performance improvement of the entire double regulated hydraulic turbine, especially in the case of keeping the existing elbow draft tube.

Dynamically induced magnetism in KTaO3

Dynamical multiferroicity features entangled dynamic orders: fluctuating electric dipoles induce magnetization. Hence, the material with paraelectric fluctuations can develop magnetic signatures if dynamically driven. We identify the paraelectric KTaO3 (KTO) as a prime candidate for the observation of the dynamical multiferroicity. We show that when a KTO sample is exposed to a circularly polarized laser pulse, the dynamically induced ionic magnetic moments are of the order of 5% of the nuclear magneton per unit cell. We determine the phonon spectrum using ab initio methods, and we identify T1u as relevant phonon modes that couple to the external field and induce magnetic polarization. We also predict a corresponding electron effect for the dynamically induced magnetic moment, which is enhanced by several orders of magnitude due to the significant mass difference between electron and ionic nucleus.Received 12 March 2021Revised 9 April 2021Accepted 14 April 2021DOI:https://doi.org/10.1103/PhysRevResearch.3.L022011Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasLaser applicationsMagnetization dynamicsPhononsPhysical SystemsMultiferroicsParaelectricsPerovskitesPropertiesMagnetic momentPolarizationTechniquesDensity functional theoryTerahertz spectroscopyCondensed Matter, Materials & Applied Physics

Reimagining “Collaborative Exploration”—A Signature Pedagogy for Sustainability in Early Childhood Education and Care

The purpose of this article is to identify the components and features of a signature pedagogy for sustainability in early childhood education and care to respond to the call for tradition and innovation in early childhood education. Collaborative exploration is proposed as a pedagogical strategy, a relevant mode of action for sustainable practice. This is a conceptual article that recalls the origins of early childhood pedagogy and uses an exemplary empirical narrative from a recent study to illustrate collaborative exploration in an early childhood educational setting. The outlining of the key features of collaborative exploration is furthermore inspired by dialogism. This article provides an argument against mainstream understandings of pedagogical strategies for early childhood education, which are often based on instrumental program approaches, emphasizing the transmission of information in a traditional classroom setting. It is argued that practices of collaborative exploration are embodied in a way that is aligned with the tradition of child-centered early years pedagogy. Moreover, they are crucial to ensuring that all participating children are given responsive support to become members of ecologically, socially and culturally sustainable educational practices, strengthening children’s resilience and agency and inclusive education. The article’s value lies in its potential to support teachers’ thinking and practice in recognizing and articulating collaborative exploration as a signature pedagogy.

Retrofitting traditional buildings: a risk-management framework integrating energy and moisture

Traditional buildings constitute a large proportion of the building stock in many countries worldwide; around 40% of the UK’s housing stock was built before 1940 and was primarily made with solid masonry walls. Only 11% of UK solid-walled dwellings had insulation installed, suggesting the high potential of the low-carbon retrofit of traditional buildings. However, there is evidence of the occurrence of unintended consequences, often associated with excess moisture. A method is presented for moisture risk management that includes the development of a process and a framework. These tools are then integrated into a novel framework for the combined energy and moisture performance retrofit of traditional buildings. An example of the framework’s practical application is provided, with a focus on retrofit measures for solid-wall insulation. The proposed systematic approach demonstrates the interconnected nature of energy and moisture. It harmonises the principles needed to support organisations in the delivery of robust retrofit of traditional buildings through the integration of pre-retrofit building assessment and post-retrofit monitoring in the process. The risk-management process and framework presented can be valuable tools to support designers in providing robust and scalable retrofit measures and strategies. Practice relevance An integrated energy and moisture risk-management process is presented to support designers in the retrofit of traditional buildings. This is accompanied by a framework that explains the steps required for moisture risk management at the various stages of the retrofit process. This systematic approach harmonises the principles needed to support organisations in delivering robust low-carbon retrofits and integrates pre- and post-retrofit building assessment in the process. While previous work has addressed energy and moisture management separately, this integrates the two aspects into a framework for risk management. An example illustrates the relevant modes and methods of assessment and monitoring in support of risk management. When combined with practical guidelines and training, the risk-management process and framework can be valuable tools to provide robust and scalable retrofit measures and strategies. The framework was developed within the context of the UK construction industry; it can be adapted to other contexts.

Quasi-Markovian property of strong wave turbulence.

This paper is concerned with the reduced-order modeling of the strongly nonlinear wave turbulence system. The motivation for such an attempt comes from the utility of the probabilistic coarse-grained model in facilitating the theoretical and numerical analysis of the true dynamical system model. One typical practice of simplifying the complex physical model is, in the spirit of Brownian motion, to replace the nonlinear interactions by white noise forcing and linear dissipation. For the case of slowly varying longwave, the resulting Markov process is an accurate approximate model. However, this conventional scheme is highly inappropriate for the description of shortwaves because the rapidly varying turbulent signal acquires a significantly non-Markovian character resulting from the poor timescale separation between the relevant mode and the environmental wave field. To resolve the issue, we discuss a simplification technique for which the central concept is the quasi-Markovian property; a non-Markov stochastic process is referred to as quasi-Markovian if it can be represented as a component of Markovian system made by adding a finite number of auxiliary variables. Our contribution in this work is to single out the nontrivial and near resonances from the nonlinear interactions in search of the auxiliary variable. We perform a comparison analysis of the autocorrelation matrices of the true and approximate models, and numerically demonstrate the effectiveness of our Markovian formulation of the inherently non-Markov turbulent signal.

Hyperrealism in Korea in the Late 1970s

Korean hyperrealism, a style that transfers photographic imagery and conventions to the medium of painting, is one of the few art forms of the late 1970s that has yet to receive substantive re-evaluation. Contrary to some critics’ derogatory dismissals, the style raises issues of cultural identity central to the aesthetics and critical theory of art after the Korean War. This study investigates how the hybrid forms and iconographical attention paid by Korean hyperrealism to common objects of everyday life reflect Korean society at a time when sophisticated encounters of opposing socio-political identities were taking place. After reviewing the history of this little known art form, especially of its critical discourse with prevalent social currents in the Korea of the period, the present study proceeds to define its iconography in relation to its “cultural other,” American hyperrealism. Many works of Korean hyperrealism engage some of the most pressing issues of Korea in the 1970s. In terms of subject matter, the works show complicated views of the character of the urbanization policies under President Park Chunghee (Pak Chŏnghŭi 朴正熙). Formally, the works present photographic details with a monochromatic tendency, a minimal surface infused with a sense of real-time theatricality, and an image of actual objects confluent with the illusionistic details. Juxtaposing and combining many antithetical concepts in an attempt to maintain a fragile balance, Korean artists struggled to create a culturally relevant mode of modernist expression and representation, and thereby translate their experience into a distinctive artistic language that is unique to their time period.

Dynamic mode decomposition: A feature extraction technique based hidden Markov model for detection of Mysticetes' vocalisations

The detection and classification of Mysticetes' vocalisations have evoked the attention of researchers over the years because of their relevance to the marine ecosystem. These vocalisations are gathered employing different passive acoustic monitoring techniques. The vocalisation datasets are accumulated over a period; thus, they are large and cannot be easily analysed manually. Consequently, efficient machine learning (ML) tools such as the hidden Markov models (HMMs) are used extensively to automatically detect and classify these huge vocalisation datasets. As with most ML tools, the detection efficiency of the HMMs depend on the adopted feature extraction technique. Feature extraction techniques such as the Mel-scale frequency cepstral coefficient (MFCC), linear predictive coefficient (LPC), and empirical mode decomposition (EMD) have been adopted with the HMMs to detect different Mysticetes' vocalisations. This article introduces the method of dynamic mode decomposition (DMD) as a feature extraction technique that can be adopted with the HMMs for the detection of Mysticetes' vocalisations. The DMD has emerged as a robust tool for analysing the dynamics of non-stationary and non-linear signals. It is a completely data-driven tool that decomposes a signal over a certain period of time into relevant modes. Here, these spatial-temporal modes are reconstructed mathematically to form reliable feature vectors of the decomposed vocalisation signals. The performance of the proposed DMD-HMM detection technique is demonstrated using the acoustic datasets of two different Mysticetes' vocalisations: Humpback whale songs and Inshore Bryde's whale short pulse calls. In both species, the proposed DMD-HMM exhibits superior sensitivity and false discovery rate performances as compared to the MFCC-HMM, LPC-HMM, and EMD-HMM detection methods. Likewise, this proposed DMD-HMM detection method can be extended to other Mysticetes' that produce characteristics sounds.

The Frictional Force between Slug and Die in Shear Cutting after Material Separation

Frictional forces in sheet metal blanking are central in different aspects, e.g. in wear prediction, validation of simulation models or in so called slug pulling. The latter is a phenomenon where the slug is pulled out of the die by the punch after the sheet metal is separated. This leads to process disturbances reaching from a blocked belt feeder up to severe tool damage caused by the simultaneous cutting of the slug and the sheet metal strip. A sufficiently high frictional force between the slug and the die prevents this effect. Despite its importance, this force and its causes have not yet been investigated in detail. A method was developed in this paper to measure the frictional force between slug and die. A shear cutting tool with an integrated piezoelectric load cell and an inductive position sensor was used on a stamping press to cut sheet metal made of CuSn6 (R350, thickness 1 mm). The die clearance, the punch edge radii and the lubrication conditions were varied. A larger die clearance resulted in a lower frictional force while a larger punch edge radius increased it significantly. Lubrication reduced the frictional force, especially for small die clearances. Finally, the cause of the frictional force was investigated by identifying the relevant springback modes of the slugs. This was carried out by correlating the slugs' deflection, oversize, and clean cut height with the frictional force. Especially the slug oversize, i.e. the difference between the slug's diameter and the die's inner diameter, revealed a strong correlation. Calculations showed that the deformation in radial direction is the main cause of the frictional force between slug and die. It suggests that the slug oversize is a good measure for the magnitude of the frictional force.

Application of Computer Technology in Vocal Music Teaching

Since the 1990s, computer technology has gradually developed and has been widely used in various fields of society. Vocal music education may be affected by computer technology. With the entry of computers into thousands of households, the number of people using network learning increases, and vocal music education also ushers in opportunities. With the continuous maturity of computer technology, the development of relevant education model, improve the efficiency and performance of education, cultivate more things. In vocal music education, the rational use of computer technology can integrate text, sound, animation and influence, in order to make students understand and master the abstract vocal music knowledge. The introduction of digital technology in phonetic education can make vocal music education more intuitive. The content of digital music education includes multimedia music education, digital music production and online music education. Students can receive education from all aspects, expand the field of education and improve artistic performance. With the continuous development of computer technology, it emerges as the times require under the new normal and is closely related to various fields of social construction. As one of the development forms of educational activities in the era of big data, computer technology has the advantages of advanced technology, rich resources, diversified forms and strong interactivity. Therefore, it can improve the comprehensive quality of education, and the development of relevant teaching modes is widely concerned in the field of education. Objectively, it creates convenient conditions for students’ comprehensive learning, independent development and in-depth exploration. With the development of computer technology, in order to improve the effect of college vocal music education, computer technology is widely used in various fields of society. It plays a role in promoting the development of various fields of society. At the same time, with the application of computer education technology in vocal music education, the teaching methods and teaching methods of vocal music education have also changed. In vocal music education, the discussion of computer technology has become an important reality to improve the quality and efficiency of vocal music education. This article, as the starting point and specific application of computer technology in vocal music education, explores the methods to improve the quality and efficiency of vocal music education, and studies and discusses the application characteristics and value of computer technology in vocal music education.

Self-administration of inhaled delta-9-tetrahydrocannabinol and synthetic cannabinoids in non-human primates.

Cannabis and synthetic cannabinoids are abused in spite of possible adverse health consequences. The current study investigated the reinforcing effects of an ecologically relevant mode of administration (inhalation) of delta-9-tetrahydrocannabinol (THC), the primary psychoactive component of cannabis, and three synthetic cannabinoids detected in synthetic cannabinoid products (JWH-018, JWH-073, and HU-210) in non-human primates (NHPs). Male and female (N = 4 each) rhesus macaques were trained to inhale warm air via a metal stem to receive a candy reinforcer, an alcohol aerosol vehicle was then paired with the candy. Dose-dependent responding for inhaled aerosols of THC (2.0-16.0 μg/kg/inhalation), JWH-018 (0.2-1.6 μg/kg/inhalation), JWH-073 (2.0-8.0 μg/kg/inhalation), and HU-210 (1.0-8.0 μg/kg/inhalation) was established using a fixed-ratio five schedule of reinforcement and compared to vehicle (alcohol) self-administration. Dose-dependent responding for inhaled heroin (25.0-100.0 μg/kg/inhalation), a known reinforcer in NHPs, was also established. Responding approximated vehicle levels for many drug doses tested, but at least half of the monkeys responded for ≥ one dose of each cannabinoid and heroin above vehicle, with the exception of THC. Drug deliveries calculated as percent vehicle followed a prototypical inverted-U shaped dose-response curve for cannabinoids and heroin except for THC and JWH-018 (in males). Grouped data according to sex demonstrated that peak percent of vehicle reinforcers earned for THC was greater in males than females, whereas peak percent of vehicle reinforcers earned for JWH-018, HU-210, and heroin were greater in females than males. These findings indicate minimal reinforcing effects of CB1 receptor agonists when self-administered by NHPs via aerosol inhalation. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Ship behavior prediction via trajectory extraction-based clustering for maritime situation awareness

This study presents a method in which historical AIS data are used to predict the future trajectory of a selected vessel. This is facilitated via a system intelligence-based approach that can be subsequently utilized to provide enhanced situation awareness to navigators and future autonomous ships, aiding proactive collision avoidance. By evaluating the historical ship behavior in a given geographical region, the method applies machine learning techniques to extrapolate commonalities in relevant trajectory segments. These commonalities represent historical behavior modes that correspond to the possible future behavior of the selected vessel. Subsequently, the selected vessel is classified to a behavior mode, and a trajectory with respect to this mode is predicted. This is achieved via an initial clustering technique and subsequent trajectory extraction. The extracted trajectories are then compressed using the Karhunen–Loéve transform, and clustered using a Gaussian Mixture Model. The approach in this study differs from others in that trajectories are not clustered for an entire region, but rather for relevant trajectory segments. As such, the extracted trajectories provide a much better basis for clustering relevant historical ship behavior modes. A selected vessel is then classified to one of these modes using its observed behavior. Trajectory predictions are facilitated using an enhanced subset of data that likely correspond to the future behavior of the selected vessel. The method yields promising results, with high classification accuracy and low prediction error. However, vessels with abnormal behavior degrade the results in some situations, and have also been discussed in this study.

Cooperative ship formation system and control methods in the ship lock waterway

To improve the safety and efficiency when ships pass through a lock, a Cooperative Ship Formation System (CSFS) in the lock waterway is proposed. An improved ship formation structure with the combination of leader–follower and behaviour-based structure is designed, and the relevant control modes are described according to the process of ship formation passing through the lock. MilliMetre-Wave (MMW) radars are introduced for the perception of ship states. Moreover, speed control, stop control and distance keeping control methods are proposed, which are related to the distance keeping control mode, speed control mode, stop control mode, stop-finished mode and emergency stop mode. Finally, a real CSFS platform with three different engineering ships was implemented in the Gezhouba Lock waterway to verify the effectiveness of CSFS and proposed control methods. Several experimental tests were carried out with the CSFS platform. The experiment results show that: 1) the average tracking error of the distance keeping control is 2.43 m; 2) the average speed control error of the leading ship is 0.08 m/s; 3) the leading ship can stop at around 2.0 m to the stop line, and both the leading ship and the following ship can switch smoothly between the different control modes.

Indoor Model Simulation for COVID-19 Transport and Exposure.

Transmission of respiratory viruses is a complex process involving emission, deposition in the airways, and infection. Inhalation is often the most relevant transmission mode in indoor environments. For severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the risk of inhalation transmission is not yet fully understood. Here, we used an indoor aerosol model combined with a regional inhaled deposited dose model to examine the indoor transport of aerosols from an infected person with novel coronavirus disease (COVID-19) to a susceptible person and assess the potential inhaled dose rate of particles. Two scenarios with different ventilation rates were compared, as well as adult female versus male recipients. Assuming a source strength of 10 viruses/s, in a tightly closed room with poor ventilation (0.5 h−1), the respiratory tract deposited dose rate was 140–350 and 100–260 inhaled viruses/hour for males and females; respectively. With ventilation at 3 h−1 the dose rate was only 30–90 viruses/hour. Correcting for the half-life of SARS-CoV-2 in air, these numbers are reduced by a factor of 1.2–2.2 for poorly ventilated rooms and 1.1–1.4 for well-ventilated rooms. Combined with future determinations of virus emission rates, the size distribution of aerosols containing the virus, and the infectious dose, these results could play an important role in understanding the full picture of potential inhalation transmission in indoor environments.

Gravitational Wave in f(R) Gravity: Possible Signature of Sub- and Super-Chandrasekhar Limiting-mass White Dwarfs

Abstract After the prediction of many sub- and super-Chandrasekhar (at least a dozen for the latter) limiting-mass white dwarfs (WDs), hence apparently a peculiar class of WDs, from the observations of luminosity of Type Ia supernovae, researchers have proposed various models to explain these two classes of WD separately. We earlier showed that these two peculiar classes of WD, along with the regular WD, can be explained by a single form of the f(R) gravity, whose effect is significant only in the high-density regime, and it almost vanishes in the low-density regime. However, since there is no direct detection of such a WD, it is difficult to single out one specific theory from the zoo of modified theories of gravity. We discuss the possibility of direct detection of such a WD in gravitational wave (GW) astronomy. It is well known that in f(R) gravity more than two polarization modes are present. We estimate the amplitudes of all the relevant modes for the peculiar and the regular WD. We further discuss the possibility of their detections through future-based GW detectors, such as LISA, ALIA, DECIGO, BBO, or the Einstein Telescope, and thereby put constraints on or rule out various modified theories of gravity. This exploration links the theory with possible observations through GW in f(R) gravity.