Little is known about the association between iodine nutrition status and bone health. The present study aimed to explore the connection between iodine nutrition status, bone metabolism parameters, and bone disease (osteopenia and osteoporosis). A cross-sectional survey was conducted involving 391, 395, and 421 adults from iodine fortification areas (IFA), iodine adequate areas (IAA), and iodine excess areas (IEA) of China. Iodine nutrition status, bone metabolism parameters and BMD were measured. Our results showed that, in IEA, the urine iodine concentrations (UIC) and serum iodine concentrations (SIC) were significantly higher than in IAA. BMD and Ca2+ levels were significantly different under different iodine nutrition levels and the BMD were negatively correlated with UIC and SIC. Univariate linear regression showed that gender, age, BMI, menopausal status, smoking status, alcohol consumption, UIC, SIC, free thyroxine, TSH, and alkaline phosphatase were associated with BMD. The prevalence of osteopenia was significantly increased in IEA, UIC ≥ 300 µg/l and SIC > 90 µg/l groups. UIC ≥ 300 µg/l and SIC > 90 µg/l were risk factors for BMD T value < –1·0 sd. In conclusion, excess iodine can not only lead to changes in bone metabolism parameters and BMD, but is also a risk factor for osteopenia and osteoporosis.

Influenced by human activities, microplastics (MPs) are widely distributed in terrestrial ecosystems. However, their ecotoxicity remains unclear. Therefore, we assessed the ecotoxicity of polyamide microplastics (PA-MPs) by investigating their toxic effects on the model insect, the silkworms Bombyx mori (Lepidoptera: Bombycidae). In this study, fifth-instar silkworm larvae were fed mulberry leaves treated with PA-MPs for 120 hours, but no changes in mortality rates were observed. However, the body weight, pupal weight, cocoon weight, egg laying amount, and cocoon shell weight in F0 generation silkworms were significantly reduced. This indicates that PA-MPs have sublethal effects on silkworms. To further investigate the effects of PA-MPs on the offspring of silkworms, we applied the age-stage, two-sex life table analysis. We found that in the PA-MPs treatment group, the duration of the larval and pupal stages of F1 generation silkworms was significantly prolonged, while the lifespan of the adults and total longevity were shortened. Meanwhile, the life history parameters (sxj, exj, lx, fxj, lxmx, and vxj values) and population parameters (R0, λ, r, and T) of F1 generation silkworms in the PA-MPs treatment group were also lower than control. This indicates that PA-MPs have transgenerational effects, affecting the growth, development, and reproduction of F1 generation silkworms. Our research findings demonstrate the sublethal and transgenerational effects of PA-MPs on silkworms, providing evidence for their ecotoxicity.

Public acceptability is crucial for the effectiveness of policy implementation. The carbon trading market is widely adopted by many countries and regions to achieve carbon neutrality and mitigate climate change. Our paper utilizes China's carbon trading market as a quasi-natural experiment, drawing on microdata from the China Residential Energy Consumption Survey to analyze the policy's impact on public acceptance of carbon pricing. We find that the carbon trading market significantly reduces the acceptability of carbon prices among households working in carbon-related industries in the pilot areas. This conclusion is still valid after a series of robustness checks. Regarding the mechanism of influence, the carbon trading market raises households' perceived costs, mainly reflected in the negative impact of rising product prices and increasing living costs. Finally, enhancing public perception of carbon, improving the distribution effect and decreasing the information asymmetry of the policy implementation can improve public acceptability of carbon prices.

The evolution of two-phase structures, turbulence/dust concentration structures, during an entire sandstorm process, including non-stationary flow, has been originally investigated in this study. Dust concentration structures are observed at different sandstorm stages, which are similar to the turbulence structures. These two-phase structures adhere to self-similarity in the steady stage but fail in the non-stationary stage. However, dust particle exhibits a better capability to follow eddies in flow, but the evolution of dust structures is not analogous to that of turbulence structures, exhibiting distinct trends. Dust particles, initiated from the ground, gradually form cluster structures in the rising stage. Their morphology exhibits a ridge-like evolutionary trend, reaching a peak in the steady stage. In contrast, turbulence structures are most persistent and oblique in the early stage but sequentially diminish in the subsequent steady and declining stages. The significant changes in shear due to sharply varying wind velocity and thermal stability are primarily responsible for these evolution differences.

While both simultaneous and sequential contests are mechanisms used in practice such as crowdsourcing, job interviews and sports contests, few studies have directly compared their performance. By modeling contests as incomplete information all-pay auctions with linear costs, we analytically and experimentally show that the expected maximum effort is higher in simultaneous contests, in which contestants choose their effort levels independently and simultaneously, than in sequential contests, in which late entrants make their effort choices after observing all prior participants’ choices. Our experimental results also show that efficiency is higher in simultaneous contests than in sequential ones. Sequential contests’ efficiency drops significantly as the number of contestants increases. We also discover that when participants’ ability follows a power distribution, high ability players facing multiple opponents in simultaneous contests tend to under-exert effort, compared to theoretical predictions. We explain this observation using a simple model of overconfidence.

Knowledge of the critical periods of crop–weed competition is crucial for designing weed management strategies in cropping systems. In the Lower Yangtze Valley, China, field experiments were conducted in 2011 and 2012 to study the effect of interference from mixed natural weed populations on cotton growth and yield and to determine the critical period for weed control (CPWC) in direct-seeded cotton. Two treatments were applied: allowing weeds to infest the crop or keeping plots weed-free for increasing periods (0, 1, 2, 4, 6, 8, 10, 12, 14, and 20 wk) after crop emergence. The results show that mixed natural weed infestations led to 35- to 55-cm shorter cotton plants with stem diameters 10 to 13 mm smaller throughout the season, fitting well with modified Gompertz and logistic models, respectively. Season-long competition with weeds reduced the number of fruit branches per plant by 65% to 82%, decreasing boll number per plant by 86% to 96% and single boll weight by approximately 24%. Weed-free seed cotton yields ranged from 2,900 to 3,130 kg ha−1, while yield loss increased with the duration of weed infestation, reaching up to 83% to 96% compared with permanent weed-free plots. Modified Gompertz and logistic models were used to analyze the impact of increasing weed control duration and weed interference on relative seed cotton yield (percentage of season-long weed-free cotton), respectively. Based on a 5% yield loss threshold, the CPWC was found to be from 145 to 994 growing degree days (GDD), corresponding to 14 to 85 d after emergence (DAE). These findings emphasize the importance of implementing effective weed control measures from 14 to 85 DAE in the Lower Yangtze Valley to prevent crop losses exceeding a 5% yield loss threshold.

This study aimed to investigate the intake of dairy products during pregnancy in women with gestational diabetes mellitus (GDM) and its impacts on neonatal birth weight and pregnancy outcomes. A total of 386 women with GDM during the second trimester pregnancy participated in this prospective cohort study. We evaluated dairy products intake through the FFQ. Pregnancy outcomes were obtained from the delivery data. Participants were divided into insufficient and sufficient intake of milk and dairy products groups (< 300 g/d and ≥ 300 g/d, respectively). The average intake of dairy products during the second trimester pregnancy in women with GDM was 317·8 ± 179·5 g/d, and the total energy intake was 1635·4 ± 708·7 kcal/d. However, 76·68 % of them did not meet the recommended total energy intake of women with GDM. After adjusting for confounding factors, women with GDM who consumed ≥ 300 g/d of dairy products had an average reduction in birth weight of 93·1 g compared with women who consumed < 300 g/d of dairy products (95 % CI −171·343, −14·927). Women with GDM in sufficient intake group was also associated with lower risk of macrosomia (95 % CI 0·043, 0·695) and caesarean section (95 % CI 0·387, 0·933) and not related to low birth weight infant (95 % CI 0·617, 14·502) and preterm birth (95 % CI 0·186, 1·510) when compared with participants in insufficient intake group. Under the premise of insufficient total energy intake, the intake of dairy products during the second trimester pregnancy in women with GDM might be related to the decrease of neonatal birth weight.

Pouch-type actuators have recently garnered significant interest and are increasingly utilized in diverse fields, including soft wearable robotics and prosthetics. This is largely due to their lightweight, high output force, and low cost. However, the inherent hysteresis behavior markedly affects the stability and force control of pouch-type driven systems. This study proposes a modified generalized Prandtl–Ishlinskii (MGPI) model, which includes generalized play operators, the tangent envelope function, and one-sided dead-zone operators, to describe the asymmetric and non-convex hysteresis characteristics of pouch-type actuators. Compared to a classical Prandtl–Ishlinskii (PI) model incorporating one-sided dead-zone functions, the MGPI model exhibits smaller relative errors at six different air pressures, demonstrating its capability to accurately describe asymmetric and non-convex hysteresis curves. Subsequently, the MGPI hysteresis model is integrated with displacement sensing technology to establish a load compensation control system for maintaining human posture. Four healthy subjects are recruited to conduct a 1 kg load compensation test, achieving efficiencies of 85.84%, 84.92%, 83.63%, and 68.86%, respectively.

The paper presents a novel control method aimed at enhancing the trajectory tracking accuracy of two-link mechanical systems, particularly nonlinear systems that incorporate uncertainties such as time-varying parameters and external disturbances. Leveraging the Udwadia–Kalaba equation, the algorithm employs the desired system trajectory as a servo constraint. First, the system’s constraints to construct its dynamic equation and apply generalized constraints from the constraint equation to an unconstrained system. Second, we design a robust approximate constraint tracking controller for manipulator control and establish its stability using Lyapunov’s law. Finally, we numerically simulate and experimentally validate the controller on a collaborative platform using model-based design methods.

The estimation of workspace for parallel kinematic machines (PKMs) typically relies on geometric considerations, which is suitable for PKMs operating under light load conditions. However, when subjected to heavy load, PKMs may experience significant deformation in certain postures, potentially compromising their stiffness. Additionally, heavy load conditions can impact motor loading performance, leading to inadequate motor loading in specific postures. Consequently, in addition to geometric constraints, the workspace of PKMs under heavy load is also constrained by mechanism deformation and motor loading performance.

This paper aims at developing a new heavy load 6-PSS PKM for multi-degree of freedom forming process. Additionally, it proposes a new method for estimating the workspace, which takes into account both mechanism deformation and motor loading performance. Initially, the geometric workspace of the machine is predicted based on its geometric configuration. Subsequently, the workspace is predicted while considering the effects of mechanism deformation and motor loading performance separately. Finally, the workspace is synthesized by simultaneously accounting for both mechanism deformation and motor loading performance, and a new index of workspace utilization rate is proposed. The results indicate that the synthesized workspace of the machine diminishes as the load magnitude and load arm increase. Specifically, under a heavy load magnitude of 6000 kN and a load arm of 200 mm, the utilization rate of the synthesized workspace is only 9.9% of the geometric workspace.

A multifunctional optical diagnostic system, which includes an interferometer, a refractometer and a multi-frame shadowgraph, has been developed at the Shenguang-II upgrade laser facility to characterize underdense plasmas in experiments of the double-cone ignition scheme of inertial confinement fusion. The system employs a 266 nm laser as the probe to minimize the refraction effect and allows for flexible switching among three modes of the interferometer, refractometer and multi-frame shadowgraph. The multifunctional module comprises a pair of beam splitters that attenuate the laser, shield stray light and configure the multi-frame and interferometric modules. By adjusting the distance and angle between the beam splitters, the system can be easily adjusted and switched between the modes. Diagnostic results demonstrate that the interferometer can reconstruct electron density below 1019 cm–3, while the refractometer can diagnose density approximately up to 1020 cm–3. The multi-frame shadowgraph is used to qualitatively characterize the temporal evolution of plasmas in the cases in which the interferometer and refractometer become ineffective.

This paper proposes an online robust self-learning terminal sliding mode control (RS-TSMC) with stability guarantee for balancing control of reaction wheel bicycle robots (RWBR) under model uncertainties and disturbances, which improves the balancing control performance of RWBR by optimising the constrained output of TSMC. The TSMC is designed for a second-order mathematical model of RWBR. Then robust adaptive dynamic programming based on an actor-critic algorithm is used to optimise the TSMC only by data sampled online. The system closed-loop stability and convergence of the neural network weights are guaranteed based on the Lyapunov analysis. The effectiveness of the proposed algorithm is demonstrated through simulations and experiments.

Pro-environmental behavior, including waste sorting and recycling, involves a combination of future-oriented (futureness) and other-oriented (otherness) attributes. Inspired by the perspective of intergenerational choice, this work explores whether eliciting concerns for future others could increase public support for recycling policy and recycling behavior. Study 1 consisted of an online random controlled trial and a laboratory experiment. In Study 1A (N = 400), future other-concern was primed using a static text manipulation, whereas in Study 1B (N = 192), a dynamic virtual manipulation was employed. The results showed that people in the conditions that elicited future other-concern reported greater household recycling intentions and more actual recycling behavior than those in the control conditions. Study 2A (N = 467) and Study 2B (N = 600) generalized this effect on the acceptance of the ‘Certain Time Certain Place’ waste sorting policy in China. Consistent with the intergenerational choice model, envisioning the future of subsequent generations is more impactful in gaining policy approval than merely envisioning a future time. These findings provide a new method for promoting public policy approval and recycling behavior, suggesting that people could become environmentally friendly when they are guided to consider future others.

A recent study published in Oryx proposed that the extinct Javan tiger Panthera tigris sondaica may still survive on the Island of Java, Indonesia, based on mitochondrial DNA analysis of a single hair sample collected from a location where a tiger was reportedly encountered. However, upon reanalysing the genetic data presented in that study, we conclude that there is little support for this claim. The sequences of the putative tiger hair and Javan tiger museum specimens generated are not from tiger cytoplasmic mitochondrial DNA but more likely the nuclear pseudogene copies of mitochondrial DNA. In addition, the number of mismatches between the two Javan tiger sequences is unusually high for homologous sequences that are both from tigers, suggesting potential issues with data reliability. The paper provides insufficient details on quality control measures, making it impossible to rule out the possibility that errors were introduced during the analysis. Consequently, it is inappropriate to use the sequences presented in that study to infer the existence of the Javan tiger.

The disassembly of end-of-life lithium–ion batteries (EOL-LIBs) is inherently complex, owing to their multi-state and multi-type characteristics. To mitigate these challenges, a human–robot collaboration disassembly (HRCD) model is developed. This model capitalizes on the cognitive abilities of humans combined with the advanced automation capabilities of robots, thereby substantially improving the disassembly process’s flexibility and efficiency. Consequently, this method has become the benchmark for disassembling EOL-LIBs, given its enhanced ability to manage intricate and adaptable disassembly tasks. Furthermore, effective disassembly sequence planning (DSP) for components is crucial for guiding the entire disassembly process. Therefore, this research proposes an approach for the generation of HRCD sequences for EOL-LIBs based on knowledge graph, providing assistance to individuals lacking relevant knowledge to complete disassembly tasks. Firstly, a well-defined disassembly process knowledge graph integrates structural information from CAD models and disassembly operating procedure. Based on the acquired information, DSP is conducted to generate a disassembly sequence knowledge graph (DSKG), which serves as a repository in graphical form. Subsequently, knowledge graph matching is employed to align nodes in the existing DSKG, thereby reusing node sequence knowledge and completing the sequence information for the target disassembly task. Finally, the proposed method is validated using retired power LIBs as a case study product.

Spray formed by a myriad of secondary droplets generated by the impact of raindrops on a deep-water pool is studied with a laboratory rain facility. Experiments are performed with two rain rates and raindrops fall on the water surface at a nearly constant velocity. The secondary droplets at various heights above the pool's water surface are recorded with a cinematic digital in-line holographic technique that consists of a high-speed camera, a pulsed Nd:YLF laser and associated optics. The experimental results show that in the heat-map scatter plots of radius versus velocity near the water surface of the pool, the droplets are distributed into three regions, corresponding to distinct physical mechanisms of droplet generation. It is found that the diameter distribution of the droplets in the rain field changes with height above the pool's water surfaces. Both numerical simulation and experimental data reveal that the liquid water content, due to the presence of secondary droplets, in the atmospheric surface layer decreases exponentially with increasing height.