Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate

Uncertainty estimation is an essential step in the evaluation of the robustness for deep learning models in computer vision, especially when applied in risk-sensitive areas. However, most state-of-the-art deep learning models either fail to obtain uncertainty estimation or need significant modification (e.g., formulating a proper Bayesian treatment) to obtain it. Most previous methods are not able to take an arbitrary model off the shelf and generate uncertainty estimation without retraining or redesigning it. To address this gap, we perform a systematic exploration into training-free uncertainty estimation for dense regression, an unrecognized yet important problem, and provide a theoretical construction justifying such estimations. We propose three simple and scalable methods to analyze the variance of outputs from a trained network under tolerable perturbations: infer-transformation, infer-noise, and infer-dropout. They operate solely during inference, without the need to re-train, re-design, or fine-tune the model, as typically required by state-of-the-art uncertainty estimation methods. Surprisingly, even without involving such perturbations in training, our methods produce comparable or even better uncertainty estimation when compared to training-required state-of-the-art methods.Comment: 18 pages, 13 figure

What drives public acceptance of chemical industrial park policy and project in China?

Chemical industrial park (CIP) policy is becoming a vital national strategy of circular economy in China and a means to enhance energy and resource efficiency, environmental performance, and economic competitiveness. It also aims to avoid environmental risks of the decentralized chemical plants that have been a subject of public protests as local citizens’ fear for chemical pollution and human's health. Public acceptance is therefore a major factor determining the success of CIP policy and project. This paper aims to investigate what drives public acceptance and rejection of chemical industrial park policies and projects in China. Our focus is on citizens in three coastal cities located in high environmental and risk sensitive areas: Dalian at Liaoning Province, Maoming at Guangdong Province, and Xiamen at Fujian Province. This is where several chemical industrial parks are (proposed) located. Based on surveys in these three representative cities, we have examined the nature and level of public acceptance towards chemical industrial park policies and projects. Results show that respondents were more positive towards the national policy, but more negative of CIP policy at the city and project level. Public acceptance of CIP policy and project was significantly influenced by factors including income, environmental value, perceived risks, procedural justice, distributive justice, benefits of CIP, and the residential distance to a CIP project. The identified factors provide a basis for anticipating and understanding likely public acceptance and should be considered in decision-making of CIP policy and project.</p

Comparing centralized and decentralized bio-energy systems in rural China

Biomass energy development has become part of the national energy strategy in China. The dis-/advantages of decentralized and centralized bio-energy systems are evaluated. Bio-energy systems should be selected based on the local circumstances. a r t i c l e i n f o t r a c t Under the dual pressures of an energy crisis and rising greenhouse gas emissions, biomass energy development and utilisation has become part of the national energy strategy in China. The last decade has witnessed a strong promotion of both centralised and decentralised bio-energy systems in rural China. The government seems to have a strong preference for centralised (village-based) bio-energy systems in recent years. However, these government-driven systems have not worked without difficulties, particularly regarding economic and technological viability and maintenance. Studies on the advantages and disadvantages of decentralised and centralised bio-energy systems are rare. This study aims to shed light on the performances of these two systems in terms of social, economic and environmental effects. Through interviewing local officials and village leaders and surveying farmers in 12 villages in Shandong Province, it was found that bio-energy systems should be selected based on the local circumstances. The diversity of the local natural, economic and social situations determines the size, place, technology and organisational model of the bio-energy system

Syntropic spin alignment at the interface between ferromagnetic and superconducting nitrides

The magnetic correlations at the superconductor/ferromagnet (S/F) interfaces play a crucial role in realizing dissipation-less spin-based logic and memory technologies, such as triplet-supercurrent spin-valves and "{\pi}" Josephson junctions. Here we report the coexistence of an induced large magnetic moment and a crypto ferromagnetic state at high-quality nitride S/F interfaces. Using polarized neutron reflectometry and d. c. SQUID measurements, we quantitatively determined the magnetization profile of S/F bilayer and confirmed the induced magnetic moment in the adjacent superconductor only exists below TC. Interestingly, the direction of the induced moment in the superconductors was unexpectedly parallel to that in the ferromagnet, which contrasts with earlier findings in S/F heterostructures based on metals or oxides. The first-principles calculations verify the observed unusual interfacial spin texture is caused by the Heisenberg direct exchange coupling through d orbital overlapping and severe charge transfer across the interfaces. Our work establishes an incisive experimental probe for understanding the magnetic proximity behavior at S/F interfaces and provides a prototype epitaxial building block for superconducting spintronics.Comment: 21 pages, 5 figures, supplementary file with 14 figure

Near-real-time monitoring of global CO₂ emissions reveals the effects of the COVID-19 pandemic

The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO₂) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO₂ emissions (−1551 Mt CO₂) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially

Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic

The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (−1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially

Wasted cities in urbanizing China

Urbanization is a characteristic of the 21st century, especially in countries with developing economies and a large amount of rural-to-urban migration. In China, the emergence of "wasted cities and towns" has paralleled urban expansion; large newly built areas that remain unpopulated and have created significant economic and social costs. We conducted a systematic investigation into the prevalence and geographical distribution of these "wasted cities and towns" through an analysis of spatially-detailed data from 1992 to 2014, and by estimating the environmental impacts of these "wasted" cities using available data in mainland China. Between 2008 and 2012, at least 28 ghost cities/towns were documented within 16 provinces, with severe effects on land use and the ecosystem, creating a waste of resources and energy. These cities contributed to poor air quality and climate change, and created unneeded construction and demolition waste. To prevent a further increase in wasted cities, and to turn existing ones into sustainable cities, China has to dramatically change its urbanization and housing policies in tandem with strengthening environmental policies, while taking long-term prevention and short-term execution strategies. Knowing how to manage the phenomenon of "wasted cities" in China is not just an environmental question, but also has strong effects on urbanization and sustainability. Developing reasonable management plans may establish an example for developing countries, and emerging economies in particular. The sustainability of urbanization might be affected if the problems identified here are not resolved. China's experiences with the environmental challenges of urbanization may provide valuable lessons for other emerging economies if the measures recommended here are implemented successfully

Three-Dimensional Force Decouping-Sensing Soft Sensor with Topological Elastomer

Sensing the deformation of soft sensor elastomer can realize the flexible operation of soft robot and enhance the perception of human-computer interaction. The structural configuration of elastomer and its elastic deformation force transfer path are crucial for decoupling sensing and studying the sensing performance of three-dimensional force soft sensor. In this article, we present a theoretical method for soft sensor with three-dimensional force decoupling-sensing. First, the constraint types of parallel manipulator with three translational motion characteristics are analyzed and used to set the constraint conditions for topology optimization. In addition, the differential kinematic modeling method is adopted to establish the differential kinematic equation of the three translations parallel manipulator, which is used as a pseudo-rigid body model for sensor information perception. Second, combining the kinematic Jacobi matrix with solid isotropic material with penalization the (SIMP), the topological model is built for designing of sensor elastomer. We optimized the composition of the material and evaluate the model’s sensing capabilities. The results validate a elastomer of soft sensor for unity between structural stiffness and perceived sensitivity

Payments for Watershed Ecosystem Services in the Eyes of the Public, China

Recent decades have witnessed an increased development of schemes for payment for watershed ecosystem services (PWES). However, the public is usually excluded from PWES systems. Reliable and empirical research on PWES from the public perspective is scarce. Aiming to understand public perceptions, attitudes, participation, and responses to PWES, this paper investigated local residents living in the Yongding River watershed area through a face-to-face questionnaire survey. The results showed that the public had limited knowledge of PWES. The public was keen to be involved in PWES decision-making, but the current level of public participation was very low. Regarding willingness to pay (WTP) and willingness to accept (WTA), nearly 55% of the respondents supported paying the upstream residents for protecting the environment if they were beneficiaries in the downstream areas, while 85% of the respondents agreed to accept compensation if they were contributors to environmental improvement in the upstream areas. Although some of the respondents&rsquo; daily lives were affected by the watershed environment, they were reluctant to pay, reflecting a sign of &ldquo;free-riding&rdquo;. The regression analysis showed that public concerns, values, knowledge of PWES and the watershed environment, and demographic factors determined the WTP and WTA. The results of the contingent valuation method and opportunity costs method showed that the annual payment for headwater conservation areas (Huailai and Yanqing) ranged from CNY 245 to 718 million (USD 36 to 106 million). This study contributes to our limited knowledge and understanding of public sentiment and makes recommendations for improving public receptivity to PWES