Deep neural networks can be employed for estimating the direction of arrival (DOA) of individual sound sources from audio signals. Existing methods mostly focus on estimating the DOA of each source on individual frames, without utilizing the motion information of the sources. This paper proposes a method for estimating trajectories of sources, leveraging the differential of trajectories across different time scales. Additionally, a neural network is employed for enhancing the trajectories wrongly estimated especially for sound sources with low-energy. Experimental evaluations conducted on simulated dataset validate that the proposed method achieves more precise localization and tracking performance and encounters less interference when the sound source energy is low.
Chlorinated paraffins (CPs), mainly short-chain CPs (SCCPs) and medium-chain CPs (MCCPs), are currently the most produced and used industrial chemicals related to persistent organic pollutants (POPs) globally. These chemicals are widely detected in the environment and in the human body. As the release of SCCPs and MCCPs from products represents only a small fraction of their stock in products, the potential long-term release of CPs from a large variety of products at the waste stage has become an issue of great concern. The results of this study showed that, by 2050, SCCPs and MCCPs used between 2000 and 2021 will cumulatively generate 226.49 Mt of CP-containing wastes, comprising 8610.13 kt of SCCPs and MCCPs. Approximately 79.72 Mt of CP-containing wastes is predicted to be generated abroad through the international trade of products using SCCPs and MCCPs. The magnitude, distribution, and growth of CP-containing wastes subject to environmentally sound disposal will depend largely on the relevant provisions of the Stockholm and Basel Conventions and the forthcoming global plastic treaty. According to multiple scenarios synthesizing the provisions of the three conventions, 26.6–101.1 Mt of CP-containing wastes will be subject to environmentally sound disposal as POP wastes, which would pose a great challenge to the waste disposal capacity of China, as well as for countries importing CP-containing products. The additional 5-year exemption period for MCCPs is expected to see an additional 10 Mt of CP-containing wastes subject to environmentally sound disposal. Thus, there is an urgent need to strengthen the Stockholm and Basel Conventions and the global plastic treaty.
This paper aims to examine the impact of the digital economy on urban entrepreneurship and its spatial spillover effects. To achieve this purpose, this research relies on data from 252 prefecture-level cities in China from 2012 to 2019. The findings demonstrate that the development of the digital economy has a positive influence on entrepreneurial activity in cities, with particularly effects observed robust at higher quantile levels. Additionally, the results suggest that urban entrepreneurial activity may be a siphoning effect, impeding entrepreneurship in neighboring cities. Furthermore, further investigation shows regional and policy heterogeneity.
Promoting rural family entrepreneurship is an effective way to realize rural revitalization. The primary aim of this study is to assess the entrepreneurial impact of family social capital on rural households in China. The objective of this study is to understand how family social capital affects rural entrepreneurship in a Chinese context. Using data from the 2020 China Family Panel Studies, this study empirically tests the effect of family social capital on rural family entrepreneurship. Research shows that family social capital is significantly and positively correlated with rural family entrepreneurship, indicating that it is an essential determinant in promoting rural family entrepreneurship. Internet use is an effective transmission path for family social capital, which affects rural entrepreneurship, and the impact of rural entrepreneurship varies with family size and household head characteristics. This study not only enriches the theoretical understanding of rural entrepreneurship but also sheds light on the behavioral mechanisms that explain the entrepreneurial process of rural households. To promote rural entrepreneurship and revitalization, it is important to be adept at activating family social capital.
Injecting CO2 when the gas reservoir of tight sandstone is depleted can achieve the dual purposes of greenhouse gas storage and enhanced gas recovery (CS-EGR). To evaluate the feasibility of CO2 injection to enhance gas recovery and understand the production mechanism, a numerical simulation model of CS-EGR in multi-stage fracturing horizontal wells is established. The behavior of gas production and CO2 sequestration is then analyzed through numerical simulation, and the impact of fracture parameters on production performance is examined. Simulation results show that the production rate increases significantly and a large amount of CO2 is stored in the reservoir, proving the technical potential. However, hydraulic fractures accelerate CO2 breakthrough, resulting in lower gas recovery and lower CO2 storage than in gas reservoirs without fracturing. Increasing the length of hydraulic fractures can significantly increase CH4 production, but CO2 breakthrough will advance. Staggered and spaced perforation of hydraulic fractures in injection wells and production wells changes the fluid flow path, which can delay CO2 breakthrough and benefit production efficiency. The fracture network of massive hydraulic fracturing has a positive effect on the CS-EGR. As a result, CH4 production, gas recovery, and CO2 storage increase with the increase in stimulated reservoir volume.
In economics and many other forecasting domains, the real world problems are too complex for a single model that assumes a specific data generation process. The forecasting performance of different methods changesChange(s) depending on the nature of the time series. When forecasting large collections of time series, two lines of approaches have been developed using time series features, namely feature-based model selection and feature-based model combination. This chapter discusses the state-of-the-art feature-based methods, with reference to open-source software implementationsImplementation.
Long and skinny molecular filaments running along Galactic spiral arms are known as “bones,” since they make up the skeleton of the Milky Way. However, their origin is still an open question. Here, we compare spectral images of HI taken by the Five-hundred-meter Aperture Spherical radio Telescope (FAST) with archival CO and Herschel dust emission to investigate the conversion from HI to H2 in two typical Galactic bones, CFG028.68-0.28 and CFG047.06+0.26. Sensitive FAST HI images and an improved methodology enabled us to extract HI narrow self-absorption (HINSA) features associated with CO line emission on and off the filaments, revealing the ubiquity of HINSA toward distant clouds for the first time. The derived cold HI abundances, [HI]/[H2], of the two bones range from ∼(0.5 to 44.7) × 10−3, which reveal different degrees of HI–H2 conversion, and are similar to those of nearby, low-mass star-forming clouds, Planck Galactic cold clumps, and a nearby active high-mass star-forming region G176.51+00.20. The HI–H2 conversion has been ongoing for 2.2–13.2 Myr in the bones, a timescale comparable to that of massive star formation therein. Therefore, we are witnessing young giant molecular clouds (GMCs) with rapid massive star formation. Our study paves the way of using HINSA to study cloud formation in Galactic bones and, more generally, in distant GMCs in the FAST era.
Liquid loading presents a formidable challenge for mature gas wells, often resulting in substantial economic losses. Traditional research has predominantly centered on the analysis of gas-liquid two-phase flow within the wellbore to predict critical gas velocity or rate, aiding in identifying the onset of liquid loading. This study introduces a fully coupled compositional wellbore-reservoir simulator designed to detect liquid loading in both vertical and inclined gas wells. Leveraging the drift-flux model to evaluate flow pattern transitions, this simulator employs pressure or rate constraints at the wellhead as boundary conditions. It comprehensively captures the flow dynamics in both the wellbore and reservoir, unveiling significant changes in gas production rate, water production rate, gas velocity, flow regime, and the reserved position of the liquid film under liquid-loaded conditions. Moreover, the accumulation of liquid at the bottom hole leads to increased reservoir pressure and gas saturation near the wellbore. The simulator predicts a typical unstable production period, emphasizing its crucial role in implementing effective strategies to mitigate liquid loading. This paper investigates the capability of the coupled wellbore-reservoir model to characterize transient liquid loading phenomena from a systematic perspective. The proposed model can function as a real-time tool for predicting the status of liquid loading in gas wells.
Tryptophan (Trp) plays a critical role in the regulation of protein structure, interactions and functions through its π system and indole N–H group. A generalizable method for blocking and rescuing Trp interactions would enable the gain-of-function manipulation of various Trp-containing proteins in vivo, but generating such a platform remains challenging. Here we develop a genetically encoded N1-vinyl-caged Trp capable of rapid and bioorthogonal decaging through an optimized inverse electron-demand Diels–Alder reaction, allowing site-specific activation of Trp on a protein of interest in living cells. This chemical activation of a genetically encoded caged-tryptophan (Trp-CAGE) strategy enables precise activation of the Trp of interest underlying diverse important molecular interactions. We demonstrate the utility of Trp-CAGE across various protein families, such as catalase-peroxidases and kinases, as translation initiators and posttranslational modification readers, allowing the modulation of epigenetic signalling in a temporally controlled manner. Coupled with computer-aided prediction, our strategy paves the way for bioorthogonal Trp activation on more than 28,000 candidate proteins within their native cellular settings.
This study assesses the health benefits of better air quality by examining the causal impact of China’s stringent “2+26” regional air pollution control policy on local air quality and population health. Employing a spatial regression discontinuity design that capitalizes on the policy’s location-specific features, we present compelling evidence that the 2+26 policy results in an average reduction of 12.2 units in the local Air Quality Index (AQI) and a 47.0% decrease in per capita medical expenditure from 2014 to 2018. A one-unit reduction in AQI corresponds to a 0.88% reduction in per capita annual medical spending, equivalent to RMB 30.2 (US$4.6). These health gains stem from reduced chronic disease prevalence and improved subjective well-being. Nationally, air quality improvement during 2014–2018 could save RMB 674billion (US$104billion) annually in national direct medical costs, constituting 11.6% of national medical expenditure in 2018. Our findings underscore the substantial health and welfare gains achievable through pollution controls in developing countries.