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In the ever-evolving landscape of modern wireless communication systems, the escalating demand for seamless connectivity has propelled the imperative for avant garde, versatile, and high-performance antennas to unprecedented heights [...]

Pedestrian inertial navigation technology plays an important role in indoor positioning technology. However, low-cost inertial sensors in smart devices are affected by bias and noise, resulting in rapidly increasing and accumulating errors when integrating double acceleration to obtain displacement. The data-driven class of pedestrian inertial navigation algorithms can reduce sensor bias and noise in IMU data by learning motion-related features through deep neural networks. Inspired by the RoNIN algorithm, this paper proposes a data-driven class algorithm, RBCN-Net. Firstly, the algorithm adds NAM and CBAM attention modules to the residual network ResNet18 to enhance the learning ability of the network for channel and spatial features. Adding the BiLSTM module can enhance the network’s ability to learn over long distances. Secondly, we construct a dataset VOIMU containing IMU data and ground truth trajectories based on visual inertial odometry (total distance of 18.53 km and total time of 5.65 h). Finally, the present algorithm is compared with CNN, LSTM, ResNet18 and ResNet50 networks in VOIMU dataset for experiments. The experimental results show that the RMSE values of RBCN-Net are reduced by 6.906, 2.726, 1.495 and 0.677, respectively, compared with the above networks, proving that the algorithm effectively improves the accuracy of pedestrian navigation.

AbstractGold, silver, platinum and palladium typically crystallize with the face-centred cubic structure. Here we report the high-yield solution synthesis of gold nanoribbons in the 4H hexagonal polytype, a previously unreported metastable phase of gold. These gold nanoribbons undergo a phase transition from the original 4H hexagonal to face-centred cubic structure on ligand exchange under ambient conditions. Using monochromated electron energy-loss spectroscopy, the strong infrared plasmon absorption of single 4H gold nanoribbons is observed. Furthermore, the 4H hexagonal phases of silver, palladium and platinum can be readily stabilized through direct epitaxial growth of these metals on the 4H gold nanoribbon surface. Our findings may open up new strategies for the crystal phase-controlled synthesis of advanced noble metal nanomaterials.

This paper evaluates the performance of a recently patented rotationally asymmetrical dielectric totally internally reflective concentrator (RADTIRC) under diffuse radiation. The RADTIRC has a geometrical concentration gain of 4.969 and two half acceptance angles of ± 30° and ± 40° along the x-axis and z-axis respectively. Simulation and experimental work have been carried out to determine the optical concentration gain under diffuse radiation. It was found that the RADTIRC has an optical concentration gain of 1.94 under diffuse irradiance. The experimental results for the single concentrator showed an optoelectronic gain of 2.13, giving a difference of 9.8% due to factors such as the presence of direct radiation during experiments, the increase in diffuse radiation due to the reflection from surrounded buildings as well as from the ground reflection.

Abstract The article introduces the process of deep energy retrofit carried out on a residential building in the UK, using a ‘TCosy’ approach in which the existing building is completely surrounded by a new thermal envelope. It reports on the entire process, from establishing the characteristics of the existing building, carrying out design simulations, documenting the off- site manufacture and on-site installation, and carrying out instrumental monitoring, occupant studies and performance evaluation. Multi-objective optimisation is used throughout the process, for establishing the characteristics of the building before the retrofit, conducting the design simulations, and evaluating the success of the completed retrofit. Building physics parameters before and after retrofit are evaluated in an innovative way through simulation of dynamic heating tests with calibrated models, and the method can be used as quality control measure in future retrofit programmes. New insights are provided into retrofit economics in the context of occupants’ health and wellbeing improvements. The wide scope of the lessons learnt can be instrumental in the creation of continuing professional development programmes, university courses, and public education that raises awareness and demand. These lessons can also be valuable for development of new funding schemes that address the outstanding challenges and the need for updating technical reference material, informing policy and building regulations.

Societal relations in rural areas have entered into a new stage of adjustment over the past decade. However, the adjustment, which might bring about profound societal changes in countryside as well as in China as a whole, have not been paid much attention and very few studies have been conducted from the perspective of ecological resource crises. We use the case of a village as an example to show how water pollution, as one of the contributory factors, possibly affect the transition of clans and societal changes in Chinese villages. Through observation and interviews, we find that there is an apparent rise of “New Clanism” within clans, which gradually abandons the tradition of supremacy of clan interests and places family or individual interests at top priority. We also find that clan boundaries get increasingly obscure since the integrity of clans is undermined by the rise of new interest groups across clans, but the boundaries remain relatively clear due to the consistency (albeit incomplete) of clan interests. Some new clan élites and representatives of new interest groups get involved in village governance, which indicates that their goals have shifted from natural resources to social or political capital. The significance of our findings is that they provide not only a unique perspective for the interaction between society and resources, but also some new ideas for the future study of rural China at the environment-social interface.

We researched China's climate and sustainable development goal with relevant and susceptible instruments capable of inducing and mitigating carbon emissions. Amidst the contributor to the global carbon emissions, China is caught in between mitigating its carbon emission and aiming towards placing its national contribution of emissions to the acceptable levels of 1.5 °C and below 2 °C. Following the intricacies surrounding China's sustainable development as it contains its economic and environmental performance, we adopt China's data of 1980 and 2018 with different scientific approaches (nonlinear autoregressive distributed lag (NARDL), dynamic ordinary least square test, and bootstrap Granger causality) with different instruments (such as economic growth, financial development, renewable energy, and innovation policies) to research China's sustainable development. For clear exposition and insight into our findings with policies attached, we draw a conclusion from the outcomes of the mentioned approaches. From NARDL and dynamic ordinary least squares (DOLS), we find that economic growth through economic activities is statistically significant in determining the trend (increase) of carbon emissions in China in both periods (short run and long run). However, other selected instruments (financial, renewable, and innovation policies) tend towards controlling and moderating the carbon emissions in China. Thus, China has good prospects to mitigate its carbon emissions if considered tailoring its policies towards favorable instruments. From bootstrap Granger causality, we find similar inferential results that support previous findings thereby confirming the positive implication of the selected instruments to China's sustainable development. Hence, the nexus that is established among the selected instruments clearly show the importance of technological innovation and renewable energy in mitigating carbon emissions.