Diagnosis and treatment are crucial steps in the process of medicalization, in which medical labels are enacted into disease realities. This article focuses on the clinical practice of pediatric ...psychiatrists， and seeks to advance our understanding of medicalization by providing a "thick description" of this practice. The article analyzes the clinical practice of doctors diagnosing children with Attention Deficit Hyperactivity Disorder （ADHD） and prescribing medication. It also examines the different actions taken by parents in this process， such as cooperation， hesitation， or capitulation. The medical attributes of ADHA as a neurodevelopmental disorder is not only embedded in the interactive relationships and collaboration networks of medicine， education， and family， but also linked to the clinical practice of diagnosis and treatment. By focusing on clinical practice， the article brings the "human" and moral dimensions of medicalization to the forefront， and in so doing， presents a vivid account of how menta
Energy is the material basis for the development of national economy. However, energy shortages become increasingly serious as a result of the growing population and the modernization of the global ...economy. Therefore, investigating drivers of energy consumption is crucial to coordinate the relationship between energy and national economic growth. This study aimed to uncover the effects of energy prices (EP), urbanization (URN) and GDP on per capita energy consumption (EC) with considering the income gaps between countries. The paper adopted the Granger causality test approach and the impulse response function analysis by using long-term time series data on EC, EP, URN and GDP during 1980–2015 in 186 countries divided into three groups (high-income, upper- and lower-middle income groups). The results indicated a long-term co-integration relationship among these variables. Granger causality test showed a bidirectional causality between URN and EC in high and lower-middle income countries but no causality in the upper-middle income group. In all groups, there is a bidirectional causal link between GDP and EC. The results of IRF showed that as urbanization level improves, its role in promoting EC become less significant. Moreover, EP affected EC negatively both in high and lower-middle income countries, but it has a positive impact on EC in upper-middle income countries. The study supports the finding that urbanization is an important factor affecting energy consumption per capita, although its contributions vary across income groups, which offers a new pathway to control the excessive growth of energy consumption.
•Analyzing energy, urbanization, economy and prices in 186 countries for 1980–2015.•An extra analysis for 87 individuals through integration techniques with panel data.•Economic growth and urbanization took a different role in different income groups.•Energy prices was a tiny effect on per capita energy consumption.
China and India accounted for two-thirds of the world׳s rise in energy use between 2000 and 2012. This paper aimed to calculate the P (population)–A (affluence)–T (technology) effects of energy use ...in China and India – the world׳s two most populous and largest developing countries. To this end, a combination of the IPAT method and the logarithmic mean divisia index technique, and annual time-series data on population, energy consumption, and gross domestic product during 1970–2012 are used. In China, a 12.53-fold growth of energy use emissions from 1970 to 2012 is driven by a combination of rapid growth in individual income and slow growth in population, with offset by technological advancement since 1980. The accelerating rise in energy use since 2000 is a result of accelerating growth rates in individual income and a reversal of earlier declining in energy intensity (technological advancement). Unlike China, the long-term rise in energy use exceeded the long-term rise in individual income in India. In addition, a strong trend of decline in energy intensity has not yet occurred in India. Thus, a 7.39-folds growth of Indian energy use for 1970–2012 was a result of relatively rapid increase in population and relatively slow increase in income, without effective offset by technological advancement. It suggests that market-oriented economic and energy reforms need to send the correct price signal to promote energy-efficient technologies thus improving energy efficiency, which is the key to a sustainable energy future in China and India.
In this paper, machine learning algorithms are first utilized to extract features of campus network traffic, and then the multi-attention mechanism is introduced to fuse the massive features ...extracted at different scales. Unsupervised learning is used to propose a method for detecting network traffic anomalies, and simulation experiments are conducted to verify the model’s performance. The results show that the detection rates of machine learning algorithms are all above 80%, the false alarm rate basically stays below 10%. The machine algorithms have higher accuracy than other algorithms in network data flow anomaly detection. This study has important reference value for campus network security research and verifies the important role of machine learning algorithms in detecting anomalies in campus network traffic.
•The coronavirus pandemic lead to a largest reduction in carbon emissions•We analyze the relationship between historical emergencies and carbon emission•Decline in energy efficiency is the main ...reason for the retaliatory rebound•Strong stimulus policy and low oil price will hinder energy efficiency•A high possibility of carbon emission retaliatory growth in post-epidemic
Studies have shown that the COVID-19 pandemic has led to a significant drop in carbon emissions in 2020, however, it is an open question whether carbon emissions continue to decline after the COVID-19 pandemic. To forecast the changes in carbon emissions after the pandemic, this study analyzed the long-term relationship between the extreme events and carbon emissions since 1960, and short-term drivers of the changes in carbon emissions before and after the 2008 financial crisis. Extreme events cannot change the upward trend of carbon emission in the long run. Specifically, the extreme events (1973 oil crisis, the American Reserve Loan Association crisis, the disintegration of the former Soviet Union, the Asian financial crisis and the 2008 financial crisis) led to a decline in carbon emissions temporarily, however, a retaliatory rebound of carbon emission were occurred after the extreme events. The long-term relationship between extreme events and carbon emission indicate that this unfolding extreme event (COVID-19 pandemic) cannot change the trend the carbon emission, and carbon emission will be rebound after the pandemic. In addition, the decomposition results showed the main contributor to the retaliatory rebound of carbon emissions after the 2008 financial crisis was the decline in energy efficiency. The decline in energy efficiency was caused by the economic recovery plan post 2008 financial crisis, which stimulated the economy and employment at a cost of energy efficiency and environmental protection. The current economic recovery plans to deal with COVID-19 pandemic also prioritizes economic development and job creation, while ignoring energy efficiency. Therefore, the post-pandemic carbon emissions will repeat the carbon emissions after the 2008 financial crisis, i.e., there will a retaliatory rebound. To avoid the retaliatory rebound, improving energy efficiency should be included in these economic recovery plan to cope with COVID-19 pandemic.
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•Estimating the effect of the digital economy on carbon emissions, with threshold variables.•The effect of the digital economy on carbon emissions displays an inverted U-shape for ...natural resource rent.•The digital economy as a whole boost carbon emissions.
Considering that previous literature has mainly focused on the impact of the digital economy (DE) on environmental degradation, ignoring the role of natural resources, this study uses two key factors (natural resource rent and anticorruption regulation) as threshold variables to reveal the effect of natural resources on the association between DE and carbon dioxide (CO2) emissions. In doing so, the study covers 97 countries, uses annual data between 2003 and 2019, and applies a panel threshold model. The outcomes present that the influence of the DE on CO2 emissions has a single-threshold effect (i.e., there is an inverted U-shaped link between the DE and CO2 emissions) when natural resource rent is the threshold variable. Specifically, the DE significantly increases CO2 emissions when the natural resource rent is at a low-to-medium level, but the DE suppresses CO2 emissions growth when natural resource rent exceeds the threshold. Moreover, the DE drives overall CO2 emissions growth when anticorruption regulation is the threshold variable and there are double thresholds for its impact on CO2 emissions. Specifically, a rise in anticorruption regulation initially exacerbates the contribution of DE impact on CO2 emissions and then weakens it over time. Based on the results, the study proposes various implications, such as formulating a DE development strategy, considering natural resources in the development of the DE, and strengthening anti-corruption efforts in the field of environmental protection.
The COVID-19 epidemic has severely affected the world economy and energy markets. In order to alleviate the shock, stabilize the financial market, and promote economic recovery, the Fed announced an ...unlimited QE policy. In order to understand the impact of the policy on the energy market under the extreme events, the study selected WTI crude oil and coal prices from January 1, 2018 to May 7, 2021 as the research objects. Taking the two years before the epidemic, the epidemic stage was further divided into four small stages according to the three peaks of the epidemic in the US. The MF-DCCA model calculations show that coal and WTI crude oil have an interactive relationship. The risks between them are not just averaged and superimposed, but transmitted and interacted.The MF-DFA model calculation results show that due to the disorder of energy supply and demand under the epidemic, market efficiency in the first quarter of 2020 has dropped rapidly. However, market efficiency decoupled from the development of the epidemic in the second half of 2020. Especially after the announcement of the QE policy, market efficiency has improved significantly. However, under the excessive monetary policy, market efficiency declined in the first half of 2021. This shows that the policy has a certain effect on alleviating the impact of the epidemic on the energy market. But this improvement is not sustainable from the long term. As prices rise, inflation continues. In the future, the volatility and risk of the energy futures market will increase.
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•The efficiency of the energy market declined during the epidemic.•Second half of 2020 has the largest increase in market efficiency.•The coal market is less efficient than the WTI crude oil market in the first half of 2021.•Risk transmission between coal and WTI crude oil markets.•The effectiveness of QE policies in alleviating energy market turmoil is gradually weakening.
•Urban form was depicted in size, shape, and centrality.•Centrality dominated influencing nighttime SUHI.•The relationships which were size-dependent, varied across climate zones.•The optimal urban ...form for SUHI mitigation is moderately sized, dispersed, polycentric, and decentralized.
There is a growing demand for urban form optimization to mitigate urban heat island (UHI) effect. Nevertheless, how UHI responds to various urban morphological patterns is still limitedly understood, especially for cities in developing countries. Here, based on 1288 urban clusters identified automatically across China, we created a consistent analytical environment to recognize both homogeneity and heterogeneity of the relationship. Specifically, urban form was characterized from aspects of size, shape, and centrality, respectively measured using metrics of urban size, area-weighted mean shape index (AWMSI) and dispersion index (DI), entropy and Moran’s I. Then, relationships between the metrics and surface UHI (SUHI) were modelled using the ordinary least squares (OLS). Results reveal that in nighttime when stronger relationships were observed than in daytime, centrality, a feature of intra-urban development structure largely neglected by previous studies, dominated as the most influential aspect. The relationships also varied across climate zones. A two-step OLS regression further reveals them to be size-dependent. As city expanded, the rising shape irregularity created a cooling impact, while the rising centrality leaded to urban warming. Overall, this study suggests that, in addition to controlling urban expansion, the optimal urban form for SUHI mitigation is moderately dispersed, polycentric, and decentralized.
In recent years, the spontaneous combustion of coal has led to numerous gas explosions in mines that have resulted in hundreds of fatalities and very substantial damage to facilities. The present ...work developed a fully coupled model capable of simulating spontaneous coal combustion and carbon monoxide (CO) release together with methane (CH4) desorption rates, concentration distributions and migration. The aim was to evaluate the combined hazard posed by spontaneous coal combustion and CH4 build-up in mine as a result of the heat release generated by coal oxidation. The results show that the zone representing the highest degree of compound hazard is in the shape of an inclined strip located between 75 and 115 m from the working face on the inlet airway side but closer to the working face on the return airway side. Increases in the CH4 concentration in the return corner decrease as the ventilation flux increases, while the potential danger zone moves deeper into the gob. A greater initial CH4 release rate from the coal increases the size of the danger zone and moves this zone closer to the working face. The danger zone also moves away from the working face with decreases in the residual coal thickness and in the coal oxidation rate. Multivariate functions were developed to predict the positions of the gas explosive zone and the oxidation zone in the gob, and a model for assessing the risk of the compound hazard was established based on evaluating the index gas concentrations in the return corner.
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•Established a fully compound model involving coal oxidation, heat transfer and gas desorption.•The evolution of desorption and migration of CH4 in gob during exothermic oxidation of coal was described.•Distribution characteristics of potential-dangerous zone were studied.•Proposed a model for assessing the risk of the compound hazard.
This study explores whether increasing renewable energy consumption can alleviate environmental pressures (per capita carbon emissions and per capita ecological footprint) and the heterogeneity of ...the effects of increasing renewable energy consumption on the environmental pressures of countries in different income groups. We analyze 130 countries and three income groups from 1992 to 2019 based on a panel threshold regression estimation approach. The results show that (i) There is a negative relationship between renewable energy consumption and per capita ecological footprint and per capita carbon emissions, indicating that renewable energy consumption alleviates environmental pressure. (ii) When renewable energy consumption increases, the negative effects of renewable energy on per capita ecological footprint and per capita carbon emissions become more significant. This means that the more renewable energy is developed, the more it helps to alleviate environmental pressure. (iii) The inhibitory effect of renewable energy consumption on per capita ecological footprint is more significant in low-income countries than in middle-income countries. This indicates that renewable energy is more effective in reducing environmental pressures in poor countries than in rich countries.
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•The Panel Threshold Regression is developed with the panel data of 130 countries.•Renewable energy consumption has a threshold effect on the environment.•Renewable energy has an inhibitory effect on the growth of the ecological footprint.•There is a non-linear negative relationship between renewable energy and CO2.•In contrast to rich countries, poorer countries are better able to reduce environmental pressures via renewable energy.
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