Mutual fund families increasingly hold bonds and stocks from the same firm. We present evidence that dual ownership allows firms to increase valuable investments and refinance by issuing bonds with lower yields and fewer restrictive covenants, especially when firms face financial distress. Dual holders also prevent overinvestment by firms with entrenched managers. Overall, our results suggest that mutual fund families internalize the agency conflicts of their portfolio companies, highlighting the positive governance externalities of intra-family cooperation.

A dual-band angular-stable transmissive linear to circular polarization converter based on metasurface is proposed and demonstrated in this work. The converter consists of three layers. The top and bottom layers are formed by an array of double split-ring layers. The unit cell of the central layer contains a square loop nesting a slant dipole. The split-rings create two resonances, enabling dual-band operation. The slant dipole and square loop are useful for improving the quality of circular polarization conversion. It is shown that the proposed polarization converter converts the incident linearly polarized wave into circularly polarized wave with opposite polarization modes over the frequency ranges of 8.77–10.58 and 17.59–19.88 GHz. The angular stability is up to 60° for 3 dB axial ratio. Moreover, the thickness of unit cell has a wavelength below 0.06 at the lower band. Compared with other designs in the literature, the structure bears merits of wideband response, high angular stability, and low-profile property within dual-band operational region. To validate the design, a sample prototype was designed, fabricated, and measured. The measured results are in good agreement with the simulated ones.

The present study focuses on two-dimensional direct numerical simulations of shallow-water breaking waves, specifically those generated by a wave plate at constant water depths. The primary objective is to quantitatively analyse the dynamics, kinematics and energy dissipation associated with wave breaking. The numerical results exhibit good agreement with experimental data in terms of free-surface profiles during wave breaking. A parametric study was conducted to examine the influence of various wave properties and initial conditions on breaking characteristics. According to research on the Bond number ($Bo$, the ratio of gravitational to surface tension forces), an increased surface tension leads to the formation of more prominent parasitic capillaries at the forwards face of the wave profile and a thicker plunging jet, which causes a delayed breaking time and is tightly correlated with the main cavity size. A close relationship between wave statistics and the initial conditions of the wave plate is discovered, allowing for the classification of breaker types based on the ratio of wave height to water depth, $H/d$. Moreover, an analysis based on inertial scaling arguments reveals that the energy dissipation rate due to breaking can be linked to the local geometry of the breaking crest $H_b/d$, and exhibits a threshold behaviour, where the energy dissipation approaches zero at a critical value of $H_b/d$. An empirical scaling of the breaking parameter is proposed as $b = a(H_b/d - \chi _0)^n$, where $\chi _0 = 0.65$ represents the breaking threshold and $n = 1.5$ is a power law determined through the best fit to the numerical results.

The present work is devoted to the analysis of drop impact on a deep liquid pool, focusing on the high-energy splashing regimes caused by large raindrops at high velocities. Such cases are characterized by short time scales and complex mechanisms, thus they have received very little attention until now. The BASILISK open-source solver is used to perform three-dimensional direct numerical simulations. The capabilities of octree adaptive mesh refinement techniques enable capturing of the small-scale features of the flow, while the volume of fluid approach combined with a balanced-force surface-tension calculation is applied to advect the volume fraction of the liquids and reconstruct the interfaces. The numerical results compare well with experimental visualizations: both the evolution of crown and cavity, the emanation of ligaments, the formation of bubble canopy and the growth of a downward-moving spiral jet that pierces through the cavity bottom, are correctly reproduced. Reliable quantitative agreements are also obtained regarding the time evolution of rim positions, cavity dimensions and droplet distributions through an observation window. Furthermore, simulation gives access to various aspects of the internal flows, which allows us to better explain the observed physical phenomena. Details of the early-time dynamics of bubble ring entrapment and splashing performance, the formation/collapse of bubble canopy and the spreading of drop liquid are discussed. The statistics of droplet size show the bimodal distribution in time, corroborating distinct primary mechanisms of droplet production at different stages.

Attaching a wireless transmission system comprising a radio frequency (RF)-chip and a dipole antenna to dielectric material of largely different permittivity leads to strong variation of the antenna feed impedance. Due to the severe impedance mismatch between the RF-chip and the antenna, the performance of the system may deteriorate drastically. The proposed antenna provides three feed points, which show respective feed-point match to 100 Ohm balanced feeds for three different dielectric environments (free-space and half-spaces of permittivity 4 and 42, respectively). Thereby, the RF-chip incorporates three 100 Ohm balanced output ports that are connected to the antenna from whom only one can be selected to provide the output signal. The respective other two output ports are shorted by an internal switching circuit that is controlled by external DC voltages. The measurement of the reflection coefficient of the stand-alone antenna and the chip agree well with the simulations, allowing to interconnect these two components. Further, the radiation pattern of the whole system is measured for two different scenarios showing good functionalities.

This paper focuses on the design, analysis, and multi-objective optimization of a novel 5-degrees of freedom (DOF) double-driven parallel mechanism. A novel 5-DOF parallel mechanism with two double-driven branch chains is proposed, which can serve as a machine tool. By installing two actuators on one branch chain, the proposed parallel mechanism can achieve 5-DOF of the moving platform with only three branch chains. Afterwards, analytical solution for inverse kinematics is derived. The 5$\times$5 homogeneous Jacobian matrix is obtained by transforming actuator velocities into linear velocities at three points on the moving platform. Meanwhile, the workspace, dexterity, and volume are analyzed based on the kinematic model. Ultimately, a stage-by-stage Pareto optimization method is proposed to solve the multi-objective optimization problem of this parallel mechanism. The optimization results show that the workspace, compactness, and dexterity of this mechanism can be improved efficiently.

This paper examines whether changes in US presidential administration and central bank turnover during the period 1976–2016 caused regime shifts in Taylor rule deviations. Using a dynamic stochastic general equilibrium model to construct the welfare-maximizing policy rule and deviations from the optimal rule, we find evidence that politics indeed play a key role in explaining these deviations. In addition to politics, unemployment rates and the interest rate spread significantly account for regime shifts in Taylor rule deviations.

This Special Issue of the Robotica is on recent advances in field and service robotics with a focus on the use of robotic and autonomous technologies to handle tasks in harsh environments and tasks that involve the multirobot cooperation and human–robot interactions.

In this paper, a novel self-adaptive underactuated robot hand with rigid-flexible coupling fingers (SAU-RFC hand) is proposed. The seven degrees of freedom (DOFs) SAU-RFC hand is driven by four servomotors, consists of three fingers, including two side-turning (ST) fingers and one non-side-turning finger. Specially, the ST fingers can perform synchronous reverse rotation laterally with each other. Each finger with three joints and two DOFs introduces a flexible structure, and the inner part of the proximal phalanx that makes most of the contact with the object is replaced by a flexible belt. The fingers can generate flexion/extension under the pull of the flexible belt, and the middle and distal phalanxes are mechanically coupled through a four-bar linkage. In particular, the flexible belt in the inner direction of the finger will deform, while it will not deform in the outer direction since the outer is a rigid structure. The flexible belt not only plays the role of transmitting power but also has the effect of uniformizing the contact force. Due to the rigid-flexible finger structure, the developed robot hand has a higher self-adaptive grasping ability for objects with different shapes, sizes, and hardness. In addition, the kinematic and kinetic analyses of SAU-RFC hand are performed. A contact force distribution model is established for the flexible belt, which demonstrates its effect of promoting uniform force distribution theoretically. In the end, experiments are conducted on different objects to verify the performance of SAU-RFC hand.

“Picking out the impurities” is a typical scenario in production line which is both time consuming and laborious. In this article, we propose a target-oriented robotic push-grasping system which is able to actively discover and pick the impurities in dense environments with the synergies between pushing and grasping actions. First, we propose an attention module, which includes target saliency detection and density-based occluded-region inference. Without the necessity of expensive labeling of semantic segmentation, our attention module can quickly locate the targets in the view or predict the candidate regions where the targets are most likely to be occluded. Second, we propose a push–grasp synergy framework to sequentially select proper actions in different situations until all targets are picked out. Moreover, we introduce an active pushing mechanism based on a novel metric, namely Target-Centric Dispersion Degree (TCDD) for better grasping. TCDD describes whether the targets are isolated from the surrounding objects. With this metric, the robot becomes more focused on the actions around the targets and push irrelevant objects away. Experimental results on both simulated environment and real-world environment show that our proposed system outperforms several baseline approaches,which also has the capability to be generalized to new scenarios.

When conducting accident analysis, the assessment of risk is one of the important links. Moreover, with regards to crew training, risk cognition is also an important training subject. However, most of the existing researches only rely on a single or a few data sources. It is necessary to fuse the collected multi-source data to obtain a more comprehensive risk evaluation model. There are few studies on the three-dimensional (3D) multi-modal data-fusion-based trajectory risk cognition. In this paper, a fuzzy logic-based trajectory risk cognition method is proposed based on multi-model spatial data fusion and accident data mining. First, the necessity of multi-model spatial data fusion is analysed and a data-fusion-based scene map is constructed. Second, a risk cognition model fused by multiple factors, multi-dimensional spatial calculations as well as data mining results is proposed, including a novel ship boundary calculation approach and newly constructed factors. Finally, a radar chart is used to illustrate the risk, and a risk cognition system is developed. Experiment results confirm the effectiveness of the method. It can be applied to train human operators of unmanned ship systems.

This paper addresses logarithmic quantizers with dynamic sensitivity design for continuous-time linear systems with a quantized feedback control law. The dynamics of state quantization and control quantization sensitivities during “zoom-in”/“zoom-out” stages are proposed. Dwell times of the dynamic sensitivities are co-designed. It is shown that with the proposed algorithm, a single-input continuous-time linear system can be stabilized by quantized feedback control via adopting sensitivity varying algorithm under certain assumptions. Also, the advantage of logarithmic quantization is sustained while achieving stability. Simulation results are provided to verify the theoretical analysis.

DNA methylation is one of the most important epigenetic modifications in breast cancer (BC) development, and long-term dietary habits can alter DNA methylation. Cadherin-4 (CDH4, a member of the cadherin family) encodes Ca2+-dependent cell–cell adhesion glycoproteins. We conducted a case–control study (380 newly diagnosed BC and 439 cancer-free controls) to explore the relationship of CDH4 methylation in peripheral blood leukocyte DNA (PBL DNA), as well as its combined and interactive effects with dietary factors on BC risk. A case-only study (335 newly diagnosed BC) was conducted to analyse the association between CDH4 methylation in breast tissue DNA and dietary factors. CDH4 methylation was detected using quantitative methylation-specific PCR. Unconditional logistic regressions were used to analyse the association of CDH4 methylation in PBL DNA and BC risk. Cross-over analysis and unconditional logistic regression were used to calculate the combined and interactive effects between CDH4 methylation in PBL DNA and dietary factors in BC. CDH4 hypermethylation was significantly associated with increased BC risk in PBL DNA (ORadjusted (ORadj) = 2·70, (95 % CI 1·90, 3·83), P < 0·001). CDH4 hypermethylation also showed significant combined effects with the consumption of vegetables (ORadj = 4·33, (95 % CI 2·63, 7·10)), allium vegetables (ORadj = 7·00, (95 % CI 4·17, 11·77)), fish (ORadj = 7·92, (95 % CI 3·79, 16·53)), milk (ORadj = 6·30, (95 % CI 3·41, 11·66)), overnight food (ORadj = 4·63, (95 % CI 2·69, 7·99)), pork (ORadj = 5·59, (95 % CI 2·94, 10·62)) and physical activity (ORadj = 4·72, (95 % CI 2·87, 7·76)). Moreover, consuming milk was significantly related with decreased risk of CDH4 methylation (OR = 0·61, (95 % CI 0·38, 0·99)) in breast tissue. Our findings may provide direct guidance on the dietary intake for specific methylated carriers to decrease their risk for developing BC.

The aim of this study was to investigate the association between daily Se intake and postpartum weight retention (PPWR) among Chinese lactating women, and the impact of their Se nutritional status on infants’ physical development. Se contents in breast milk and plasma collected from 264 lactating Chinese women at the 42nd day postpartum were analysed with inductively coupled plasma MS. Daily Se intake was calculated based on plasma Se concentration. The dietary data of 24-h records on three consecutive days were collected. Infant growth status was evaluated with WHO standards by Z-scores. Linear regression analyses and multinomial logistic regression were conducted to examine the impact of Se disequilibrium (including other factors) on PPWR and growth of infants, respectively. The results indicated that: (1) the daily Se intake of the subjects was negatively associated with their PPWR (B = −0·002, 95 % CI − 0·003, 0·000, P = 0·039); (2) both insufficient Se daily intake (B = −0·001, OR 0·999, 95 % CI 0·998, 1·000, P = 0·014) and low level of Se in milk (B = −0·025, OR 0·975, 95 % CI 0·951, 0·999, P = 0·021) had potential associations with their infants’ wasting, and low level of Se in milk (B = −0·159, OR 0·853, 95 % CI 0·743, 0·980, P = 0·024) had a significant association with their infants’ overweight. In conclusion, the insufficient Se nutritional status of lactating Chinese women was first found as one possible influencing factor of their PPWR as well as low physical development of their offspring.

Generating designs via machine learning has been an on-going challenge in computer-aided design. Recently, deep learning methods have been applied to randomly generate images in fashion, furniture and product design. However, such deep generative methods usually require a large number of training images and human aspects are not taken into account in the design process. In this work, we seek a way to involve human cognitive factors through brain activity indicated by electroencephalographic measurements (EEG) in the generative process. We propose a neuroscience-inspired design with a machine learning method where EEG is used to capture preferred design features. Such signals are used as a condition in generative adversarial networks (GAN). First, we employ a recurrent neural network Long Short-Term Memory as an encoder to extract EEG features from raw EEG signals; this data are recorded from subjects viewing several categories of images from ImageNet. Second, we train a GAN model conditioned on the encoded EEG features to generate design images. Third, we use the model to generate design images from a subject’s EEG measured brain activity. To verify our proposed generative design method, we present a case study, in which the subjects imagine the products they prefer, and the corresponding EEG signals are recorded and reconstructed by our model for evaluation. The results indicate that a generated product image with preference EEG signals gains more preference than those generated without EEG signals. Overall, we propose a neuroscience-inspired artificial intelligence design method for generating a design taking into account human preference. The method could help improve communication between designers and clients where clients might not be able to express design requests clearly.

A flexible surface-enhanced Raman scattering (SERS) substrate was prepared by vacuum evaporation of silver on the surface of woven nylon fabrics. SERS properties of the Ag-coated nylon fabrics varied as the thickness of silver coatings changed, relative to the morphologies and distribution of silver nanoparticles (NPs) on fiber. The SERS enhancement performance of Ag-coated nylon fabrics was evaluated by collecting Raman signals of different concentrations of p-aminothiophenol (PATP). The results suggested that the nylon fabrics coated with 10 nm thickness Ag NPs coatings possessed high SERS activity and its detection concentration for PATP is as low as 10−9 M. Furthermore, sensitive SERS signals with excellent reproducibility (Relative standard deviation = 8.25%) and stability (30 days) have been demonstrated. In addition, the SERS nylon fabrics have been applied to rapidly detect thiram pesticides on cucumber, which indicated a great potential for trace analysis.

In late December 2019, patients of atypical pneumonia due to an unidentified microbial agent were reported in Wuhan, Hubei Province, China. Subsequently, a novel coronavirus was identified as the causative pathogen which was named SARS-CoV-2. As of 12 February 2020, more than 44 000 cases of SARS-CoV-2 infection have been confirmed in China and continue to expand. Provinces, municipalities and autonomous regions of China have launched first-level response to major public health emergencies one after another from 23 January 2020, which means restricting movement of people among provinces, municipalities and autonomous regions. The aim of this study was to explore the correlation between the migration scale index and the number of confirmed coronavirus disease 2019 (COVID-19) cases and to depict the effect of restricting population movement. In this study, Excel 2010 was used to demonstrate the temporal distribution at the day level and SPSS 23.0 was used to analyse the correlation between the migration scale index and the number of confirmed COVID-19 cases. We found that since 23 January 2020, Wuhan migration scale index has dropped significantly and since 26 January 2020, Hubei province migration scale index has dropped significantly. New confirmed COVID-19 cases per day in China except for Wuhan gradually increased since 24 January 2020, and showed a downward trend from 6 February 2020. New confirmed COVID-19 cases per day in China except for Hubei province gradually increased since 24 January 2020, and maintained at a high level from 24 January 2020 to 4 February 2020, then showed a downward trend. Wuhan migration scale index from 9 January to 22 January, 10 January to 23 January and 11 January to 24 January was correlated with the number of new confirmed COVID-19 cases per day in China except for Wuhan from 22 January to 4 February. Hubei province migration scale index from 10 January to 23 January and 11 January to 24 January was correlated with the number of new confirmed COVID-19 cases per day in China except for Hubei province from 22 January to 4 February. Our findings suggested that people who left Wuhan from 9 January to 22 January, and those who left Hubei province from 10 January to 24 January, led to the outbreak in the rest of China. The ‘Wuhan lockdown’ and the launching of the first-level response to this major public health emergency may have had a good effect on controlling the COVID-19 epidemic. Although new COVID-19 cases continued to be confirmed in China outside Wuhan and Hubei provinces, in our opinion, these are second-generation cases.