The safety of human-collaborative operations with robots depends on monitoring the external torque of the robot, in which there are toque sensor-based and torque sensor-free methods. Economically, the classic method for estimating joint external torque is the first-order momentum observer (MOB) based on a physic model without torque sensors. However, uncertainties in the dynamic model, which encompasses parameters identification error and joint friction, affect the torque estimation accuracy. To address this issue, this paper proposes using the backpropagation neural network (BPNN) method to estimate joint external torque without the delicate physical model by utilizing the powerful machine learning ability to handle the uncertainties of the MOB method and improve the accuracy of torque estimation. Using data obtained from the torque sensor to train the BPNN to build up a digital torque model, the trained BPNN can perceive force in practical applications without relying on the torque sensor. In the end, by contrast to the classic first-order MOB, the result demonstrates that BPNN achieves higher estimation accuracy compared to the MOB.

We present a systematic study on the effects of small aspect ratios $\varGamma$ on heat transport in liquid metal convection with a Prandtl number of $Pr=0.029$. The study covers $1/20\le \varGamma \le 1$ experimentally and $1/50\le \varGamma \le 1$ numerically, and a Rayleigh number $Ra$ range of $4\times 10^3 \le Ra \le 7\times 10^{9}$. It is found experimentally that the local effective heat transport scaling exponent $\gamma$ changes with both $Ra$ and $\varGamma$, attaining a $\varGamma$-dependent maximum value before transition-to-turbulence and approaches $\gamma =0.25$ in the turbulence state as $Ra$ increases. Just above the onset of convection, Shishkina (Phys. Rev. Fluids, vol 6, 2021, 090502) derived a length scale $\ell =H/(1+1.49\varGamma ^{-2})^{1/3}$. Our numerical study shows $Ra_{\ell }$, i.e. $Ra$ based on $\ell$, serves as a proper control parameter for heat transport above the onset with $Nu-1=0.018(1+0.34/\varGamma ^2)(Ra/Ra_{c,\varGamma }-1)$. Here $Ra_{c,\varGamma }$ represents the $\varGamma$-dependent critical $Ra$ for the onset of convection and $Nu$ is the Nusselt number. In the turbulent state, for a general scaling law of $Nu-1\sim Ra^\alpha$, we propose a length scale $\ell = H/(1+1.49\varGamma ^{-2})^{1/[3(1-\alpha )]}$. In the case of turbulent liquid metal convection with $\alpha =1/4$, our measurement shows that the heat transport will become weakly dependent on $\varGamma$ with $Ra_{\ell }\equiv Ra/(1+1.49\varGamma ^{-2})^{4/3} \ge 7\times 10^5$. Finally, once the flow becomes time-dependent, the growth rate of $Nu$ with $Ra$ declines compared with the linear growth rate in the convection state. A hysteresis is observed in a $\varGamma =1/3$ cell when the flow becomes time-dependent. Measurements of the large-scale circulation suggest the hysteresis is caused by the system switching from a single-roll-mode to a double-roll-mode in an oscillation state.

Using thermal convection in liquid metal, we show that strong spatial confinement not only delays the onset Rayleigh number $Ra_c$ of Rayleigh–Bénard instability but also postpones the various flow-state transitions. The $Ra_c$ and the transition to fully developed turbulence Rayleigh number $Ra_f$ depend on the aspect ratio $\varGamma$ with $Ra_c\sim \varGamma ^{-4.05}$ and $Ra_f\sim \varGamma ^{-3.01}$, implying that the stabilization effects caused by the strong spatial confinement are weaker on the transition to fully developed turbulence when compared with that on the onset. When the flow state is characterized by the supercritical Rayleigh number $Ra/Ra_{c}$ ($Ra$ is the Rayleigh number), our study shows that the transition to fully developed turbulence in strongly confined geometries is advanced. For example, while the flow becomes fully developed turbulence at $Ra\approx 200Ra_c$ in a $\varGamma =1$ cell, the same transition in a $\varGamma =1/20$ cell only requires $Ra\approx 3Ra_c$. Direct numerical simulation and linear stability analysis show that in the strongly confined regime, multiple vertically stacked roll structures appear just above the onset of convection. With an increase of the driving strength, the flow switches between different-roll states stochastically, resulting in no well-defined large-scale coherent flow. Owing to this new mechanism that only exists in systems with $\varGamma <1$, the flow becomes turbulent in a much earlier stage. These findings shed new light on how turbulence is generated in strongly confined geometries.

Energy loss of protons with 90 and 100 keV energies penetrating through a hydrogen plasma target has been measured, where the electron density of the plasma is about 1016 cm−3 and the electron temperature is about 1-2 eV. It is found that the energy loss of protons in the plasma is obviously larger than that in cold gas and the experimental results based on the Bethe model calculations can be demonstrated by the variation of effective charge of protons in the hydrogen plasma. The effective charge remains 1 for 100 keV protons, while the value for 90 keV protons decreases to be about 0.92. Moreover, two empirical formulae are employed to extract the effective charge.

The effects of monolaurin (ML) on the health of piglets infected with porcine epidemic diarrhoea virus (PEDV) have not been fully understood. This study aimed to investigate its role in blood biochemical profile, intestinal barrier function, antioxidant function and the expression of antiviral genes in piglets infected with PEDV. Thirty-two piglets were randomly divided into four groups: control group, ML group, PEDV group and ML + PEDV group. Piglets were orally administrated with ML at a dose of 100 mg/kg·BW for 7 d before PEDV infection. Results showed that PEDV infection significantly decreased D-xylose content and increased intestinal fatty acid-binding protein content, indicating that PEDV infection destroyed intestinal barrier and absorption function. While it could be repaired by ML administration. Moreover, ML administration significantly decreased plasma blood urea nitrogen and total protein content upon PEDV infection. These results suggested ML may increase protein utilisation efficiency. ML administration significantly decreased the number of large unstained cells and Hb and increased the number of leucocytes and eosinophils in the blood of PEDV-infected piglets, indicating ML could improve the immune defense function of the body. In the presence of PEDV infection, ML administration significantly increased superoxide dismutase and catalase activities in blood and colon, respectively, indicating ML could improve antioxidant capacity. Besides, ML administration reversed the expression of ISG15, IFIT3 and IL-29 throughout the small intestine and Mx1 in jejunum and ileum, indicating the body was in recovery from PEDV infection. This study suggests that ML could be used as a kind of feed additive to promote swine health upon PEDV infection.

According to the positive time-discounting assumption of intertemporal decision-making, people prefer to undergo negative events in the future rather than in the present. However, negative discounting has been identified in the intertemporal choice and loss domains, which refers to people’s preference to experience negative events earlier rather than later. Studies have validated and supported the "anticipated dread" as an explanation for negative discounting. This study again explored the effect of anticipated dread on intertemporal choice using content analysis; that is, having participants identify anticipated dread among reasons for negative discounting. This study also validated the effect of anticipated dread on negative discounting by manipulating anticipated dread. This study adds empirical and direct evidence for the role of anticipated dread in negative discounting.

Intertemporal choices involve tradeoffs between outcomes that occur at different times. Most of the research has used pure gains tasks and the discount rates yielding from those tasks to explain and predict real-world behaviors and consequences. However, real decisions are often more complex and involve mixed outcomes (e.g., sooner-gain and later-loss or sooner-loss and later-gain). No study has used mixed gain-loss intertemporal tradeoff tasks to explain and predict real-world behaviors and consequences, and studies involving such tasks are also scarce. Considering that tasks involving a combination of gains and losses may yield different discount rates and that existing pure gains tasks do not explain or predict real-world outcomes well, this study conducted two experiments to compare the discount rates of mixed gain-loss intertemporal tradeoffs with those of pure gains or pure losses (Experiment 1) and to examine whether these tasks predicted different real-world behaviors and consequences (Experiment 2). Experiment 1 suggests that the discount rate ordering of the four tasks was, from highest to lowest, pure gains, sooner-loss and later-gain, pure losses, and sooner-gain and later-loss. Experiment 2 indicates that the evidence supporting the claim that the discount rates of the four tasks were related to different real-world behaviors and consequences was insufficient.

The northern Alxa region is located in the central segment of the southern Central Asian Orogenic Belt. Many controversies and deficiencies still exist regarding the magma source characteristics, petrogenesis and tectonic regimes during the late Palaeozoic – early Mesozoic period within this region. This study presents whole-rock compositions and zircon U–Pb and Lu–Hf isotopic data for three early Mesozoic I- and A-type granitic plutons occurring in the northern Alxa region. The Haerchaoenji and Chahanhada I-type granitoids yielded zircon 206Pb–238U ages of 245 ± 5 Ma and 245 ± 2 Ma, respectively. The variable positive zircon ϵHf(t) values between +1.8 and +11.8, with young TDM ages of 425–837 Ma, indicate that these I-type granitoids were mainly derived from juvenile crustal materials. The Wulantaolegai pluton has a zircon 206Pb–238U age of 237 ± 2 Ma and is classified as having high-K calc-alkaline A-type affinity. Furthermore, the positive zircon ϵHf(t) values of the Wulantaolegai granite range from +3.3 to +8.7 with young TDM ages of 545–778 Ma, suggesting the involvement of a juvenile crustal source as well. Furthermore, the major-element compositions of the Chahanhada and Wulantaolegai granites suggest the input of metasedimentary components. Geochemically, the Haerchaoenji and Chahanhada I-type granitoids show an arc affinity, while the Wulantaolegai granite exhibits a post-collisional affinity. However, with regional data, we suggest that the Haerchaoenji and Chahanhada I-type granitoids were also emplaced in a post-collisional setting, and the arc affinity was probably inherited from recycled subduction-related materials. These lines of evidence obtained in this study enable us to argue that the Palaeo-Asian Ocean in the central segment of the Central Asian Orogenic Belt closed before Middle Triassic time.

We present an experimental study of Rayleigh–Bénard convection using liquid metal alloy gallium-indium-tin as the working fluid with a Prandtl number of $Pr=0.029$. The flow state and the heat transport were measured in a Rayleigh number range of $1.2\times 10^{4} \le Ra \le 1.3\times 10^{7}$. The temperature fluctuation at the cell centre is used as a proxy for the flow state. It is found that, as $Ra$ increases from the lower end of the parameter range, the flow evolves from a convection state to an oscillation state, a chaotic state and finally a turbulent state for $Ra>10^5$. The study suggests that the large-scale circulation in the turbulent state is a residual of the cell structure near the onset of convection, which is in contrast with the case of $Pr\sim 1$, where the cell structure is transiently replaced by high order flow modes before the emergence of the large-scale circulation in the turbulent state. The evolution of the flow state is also reflected by the heat transport characterised by the Nusselt number $Nu$ and the probability density function (p.d.f.) of the temperature fluctuation at the cell centre. It is found that the effective local heat transport scaling exponent $\gamma$, i.e. $Nu\sim Ra^{\gamma }$, changes continuously from $\gamma =0.49$ at $Ra\sim 10^4$ to $\gamma =0.25$ for $Ra>10^6$. Meanwhile, the p.d.f. at the cell centre gradually evolves from a Gaussian-like shape before the transition to turbulence to an exponential-like shape in the turbulent state. For $Ra>10^6$, the flow shows self-similar behaviour, which is revealed by the universal shape of the p.d.f. of the temperature fluctuation at the cell centre and a $Nu=0.19Ra^{0.25}$ scaling for the heat transport.

The treatment of water containing heavy metals has attracted increasing attention because the ingestion of such water poses risks to human health. Due to their relatively large specific surface areas and surface charges, clay minerals play a significant role in the adsorption of heavy metals in water. However, the major factors that influence the adsorption rates of clay minerals are not well understood, and thus methods to predict the sorption of heavy metals by clay minerals are lacking. A method that can identify the most appropriate clay minerals for removal of a given heavy metal, based on the predicted sorption of the clay minerals, is required. This paper presents a widely applicable deep learning neural network approach that yielded excellent predictions of the influence of the sorption ratio on the adsorption of heavy metals by clay minerals. The neural network model was based on datasets of heavy-metal parameters that are available generally. It yielded highly accurate predictions of the adsorption rate based on training data from the dataset and was able to account for a wide range of input parameters. A Pearson sensitivity analysis was used to determine the contributions of individual input parameters to the adsorption rates predicted by the neural network. This newly developed method can predict the major factors influencing heavy-metal adsorption rates. The model described here could be applied in a wide range of scenarios.

The autonomous underwater vehicle (AUV) has a problem with feature loss when recognizing small targets underwater. At present, algorithms usually use multi-scale feature extraction to solve the problem, but this method increases the computational effort of the algorithm. In addition, low underwater light and turbid water result in incomplete information on target features. This paper proposes an enhanced dilated convolution framework (EHDC) for underwater blurred target recognition. Firstly, this paper extracts small target features through hybrid dilated convolution networks, increasing the perceptive field of the algorithm without increasing the computational power of the algorithm. Secondly, the proposed algorithm learns spatial semantic features through an adaptive correlation matrix and compensates for the missing features of the target. Finally, this paper fuses spatial semantic features and visual features for the recognition of small underwater blurred targets. Experiments show that the proposed method improves the recognition accuracy by 1.04% compared to existing methods when recognizing small underwater blurred targets.

Improving grain yield and lodging resistance are two important targets for improving rice production. The aim of this study was to link grain yield and lodging resistance with growth patterns in rice. A nitrogen (N) fertilization experiment was conducted in 2020 and 2021, which consisted of two N rates (150 and 225 kg ha–1) and three N split-application ratios among the basal, early tillering, and panicle initiation stages (6:3:1, 5:3:2, and 4:3:3). The results demonstrated that increasing the N rate from 150 to 225 kg ha–1 did not affect grain yield but increased the plant lodging index by 16%. This increase in the plant lodging index was attributable to a higher plant fresh weight resulting from improved post-heading growth and a lower plant lodging load, which was partially due to a higher leaf area index. Altering the N split-application ratio from 6:3:1 to 4:3:3 increased grain yield by 4% but did not affect the plant lodging index in rice. The increase in grain yield was due to improved post-heading growth mainly resulting from increased radiation use efficiency during the post-heading period, which was partially attributable to increased specific leaf weight. An improvement in pre-heading growth in 2021 did not affect grain yield but increased the plant lodging load and decreased the plant lodging index by 36% compared to 2020. The improvement in pre-heading growth was due to a higher intercepted solar radiation resulting from higher leaf area index and incident solar radiation during the pre-heading period. The results of this study indicate that improving pre-heading growth can maintain grain yield and increase lodging resistance, while improving post-heading growth by increasing canopy radiation use efficiency (but not the leaf area index) can increase grain yield and maintain lodging resistance.

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.

The development of high-yielding, short-duration super-rice hybrids is important for ensuring food security in China where multiple cropping is widely practiced and large-scale farming has gradually emerged. In this study, field experiments were conducted over 3 years to identify the yield formation characteristics in the shorter-duration (∼120 days) super-rice hybrid ‘Guiliangyou 2’ (G2) by comparing it with the longer-duration (∼130 days) super-rice hybrid ‘Y-liangyou 1’ (Y1). The results showed that G2 had a shorter pre-heading growth duration and consequently a shorter total growth duration compared to Y1. Compared to Y1, G2 had lower total biomass production that resulted from lower daily solar radiation, apparent radiation use efficiency (RUE), crop growth rate (CGR), and biomass production during the pre-heading period, but the grain yield was not significantly lower than that of Y1 because it was compensated for by the higher harvest index that resulted from slower leaf senescence (i.e., slower decline in leaf area index during the post-heading period) and higher RUE, CGR, and biomass production during the post-heading period. Our findings suggest that it is feasible to reduce the dependence of yield formation on growth duration to a certain extent in rice by increasing the use efficiency of solar radiation through crop improvement and also highlight the need for a greater fundamental understanding of the physiological processes involved in the higher use efficiency of solar radiation in super-rice hybrids.

A compact ultrawideband (UWB) antenna with reconfigurable triple band notch characteristics is proposed in this paper. The antenna consists of a coplanar waveguide-fed top-cut circular-shaped radiator with two etched C-shaped slots, a pair of split-ring resonators (SRRs) on the backside and four p-type intrinsic n-type (PIN) diodes integrated in the slots and SRRs. By controlling the current distribution in the slots and SRRs, the antenna can realize eight band notch states with independent switch ability, which allows UWB to coexist with 5G (3.3–4.4 GHz)/WiMAX (3.3–3.6 GHz), WLAN (5.15–5.825 GHz), and X-band (7.9–8.4 GHz) bands without interference. By utilizing a nested structure of C-shaped slots and SRRs on the backside, a compact size of 18 × 19.5 mm2 is achieved along with multimode triple band notch reconfigurability. The antenna covers a bandwidth of 3.1–10.6 GHz. A prototype is fabricated and tested. The simulated and experimental results are in good agreement.

We study the scaling limit of a random forest with prescribed degree sequence in the regime that the largest tree consists of all but a vanishing fraction of nodes. We give a description of the limit of the forest consisting of the small trees, by relating a plane forest to a marked cyclic forest and its corresponding skip-free walk.