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An open letter to graduate students and other procrastinators: it’s time to write
Writer’s block is a myth There are lots of resources and varying opinions on how to write a technical paper. Whole books have been written…
Dynamic flood adaptation pathways for Shanghai under deep uncertainty
Decision-making for flood adaptation in coastal cities is complicated by deep uncertainty about sea level rise, subsidence, and socioeconomic trends, which increases the possibility of under- or over-investment. Using the megacity of Shanghai as a case study, we apply the dynamic adaptive policy pathways (DAPP) framework to demonstrate robust and flexible decision-making under uncertainty. The framework integrates compound flood risk modeling of flood risk, economic evaluation, and dynamic adaptation pathways. Our results show that without adaptation, annual damages and annual casualties could increase by 86–167%, and 45–97 times, respectively, by the year 2100. ‘Hard adaptation strategies’ such as levees can reduce projected damages by 58–94%. In contrast, local scale ‘soft adaptation’ (flood-proofing buildings) is only effective and economically efficient in combination with hard adaptation (‘hybrid strategy’). The best economic performance is a hybrid strategy that starts implementing a large storage tank adding a mix of measures around 2050 (coastal wetlands, dry-floodproofing, and land elevation). Depending on how the future plays out, a hybrid strategy of a combination of a storm-surge barrier and coastal wetlands would yield high economic benefits after ~2070.
Exploring the spatial distribution characteristics and formation mechanisms of Hakka folk settlements: a case study of Hakka traditional architecture in southeastern China
Traditional settlements are an important cultural landscape as carriers of regional culture. In order to explore the spatial distribution characteristics and causes of Hakka folk settlements, Hakka traditional architecture in southeastern China was chosen as the research object. From the perspective of geography, this paper combines methods such as survey statistics, geographic information system to calculate the spatial index of Hakka traditional architecture, analyses the spatial distribution characteristics and distribution patterns of Hakka traditional architecture within the Hakka region. The results revealed that the Hakka traditional architecture is characterized by a ‘more clustered and less scattered’ distribution, concentrated and uneven, with the Hakka settlements being spatially gathered and less dispersed. The spatial distribution of Hakka traditional architecture forms five core distribution areas as Ganzhou, Longyan, Meizhou, Huizhou and Shenzhen. The Hakka settlements are predominantly oriented in a northerly direction. The north-south orientation of the settlement dominates the traditional orientation of Hakka buildings. The Hakka traditional buildings are mainly located in areas with altitudes below 500 meters and slopes below 15°. The distance from the water system within 5 km accounts for 63.43% of the total number of Hakka traditional buildings, reflecting the proximity of Hakka traditional buildings to water. The number of square-shaped Hakka buildings is 143, the most significant number of all Hakka building types. It is evident that the formation of Hakka settlements hinges significantly on the interplay of physical and geographical conditions. The Hakka culture, water availability, climate conditions, historical migration patterns and ethnic cultural dynamics influence the distribution of Hakka traditional architecture.
Smart insect-computer hybrid robots empowered with enhanced obstacle avoidance capabilities using onboard monocular camera
Insect-computer hybrid robots are receiving increasing attention as a potential alternative to small artificial robots due to their superior locomotion capabilities and low manufacturing costs. Controlling insect-computer hybrid robots to travel through terrain littered with complex obstacles of various shapes and sizes is still challenging. While insects can inherently deal with certain obstacles by using their antennae to detect and avoid obstacles, this ability is limited and can be interfered with by control signals when performing navigation tasks, ultimately leading to the robot being trapped in a specific place and having difficulty escaping. Hybrid robots need to add additional sensors to provide accurate perception and early warning of the external environment to avoid obstacles before getting trapped, ensuring smooth navigation tasks in rough terrain. However, due to insects’ tiny size and limited load capacity, hybrid robots are very limited in the sensors they can carry. A monocular camera is suitable for insect-computer hybrid robots because of its small size, low power consumption, and robust information acquisition capabilities. This paper proposes a navigation algorithm with an integrated obstacle avoidance module using a monocular camera for the insect-computer hybrid robot. The monocular cameras equipped with a monocular depth estimation algorithm based on deep learning can produce depth maps of environmental obstacles. The navigation algorithm generates control commands that can drive the hybrid robot away from obstacles according to the distribution of obstacle distances in the depth map. To ensure the performance of the monocular depth estimation model when applied to insect-computer hybrid robotics scenarios, we collected the first dataset from the viewpoint of a small robot for model training. In addition, we propose a simple but effective depth map processing method to obtain obstacle avoidance commands based on the weighted sum method. The success rate of the navigation experiment is significantly improved from 6.7% to 73.3%. Experimental results show that our navigation algorithm can detect obstacles in advance and guide the hybrid robots to avoid them before they get trapped.
Hybrid care in mental health: a framework for understanding care, research, and future opportunities
Technology is playing an increasing role in healthcare, especially in mental health. Traditional mental healthcare, whether in-person or via telehealth, cannot by itself address the massive need for services. Standalone technology such as smartphone apps, while easily accessible, have seen limited engagement and efficacy on their own. Hybrid care – the combination of synchronous in-person or telehealth appointments with the use of asynchronous digital tools such as smartphone applications, wearable devices, or digital therapeutics – has the potential to offer the best of both worlds, providing both increased access and higher engagement and efficacy. In this paper, we present a framework highlighting the key components of hybrid care models: digital intervention, human support, and target population. This framework can be used to evaluate existing models in the literature and in practice, identify areas of need and opportunity, and serve as a blueprint for key elements to consider when designing new hybrid care models.
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