Analysis of energy consumption and change structure in major economic sectors of Pakistan.

Studying and analyzing energy consumption and structural changes in Pakistan's major economic sectors is crucial for developing targeted strategies to improve energy efficiency, support sustainable economic growth, and enhance energy security. The logarithmic mean Divisia index (LMDI) method is applied to find the factors' effects that change sector-wise energy consumption from 1990 to 2019. The results show that: (1) the change in mixed energy and sectorial income shows a negative influence, while energy intensity (EI) and population have an increasing trend over the study period. (2) The EI effects of the industrial, agriculture and transport sectors are continuously rising, which is lowering the income potential of each sector. (3) The cumulative values for the industrial, agricultural, and transport sectors increased by 57.3, 5.3, and 79.7 during 2019. Finally, predicted outcomes show that until 2035, the industrial, agriculture, and transport incomes would change by -0.97%, 13%, and 65% if the energy situation remained the same. Moreover, this sector effect is the most crucial contributor to increasing or decreasing energy consumption, and the EI effect plays the dominant role in boosting economic output. Renewable energy technologies and indigenous energy sources can be used to conserve energy and sectorial productivity.

Does digital inclusive finance promote carbon emission reduction of enterprises.

Can the information technology revolution lead to carbon emission reduction for firms? This study extends the limited evidence in the literature and investigate the role and mechanism of digital inclusive finance on enterprises' carbon emissions using panel data of 247 prefectural-level cities and 6019 industrial enterprises in China. Our findings indicate that digital inclusive finance can promote enterprise carbon emission reduction, and this effect remains significant after the instrumental variable estimation test. The effect has regional heterogeneity and the development of digital inclusive finance in the area east of Hu Huanyong line has a significant impact on reducing enterprise carbon emission. The role of digital inclusive finance is heterogeneous in enterprise ownership, with a remarkable effect in non-state-owned enterprises. Sub-dimension analysis indicates that the breadth of coverage, depth of use, and degree of digitalization of digital inclusive finance have differential effects on reducing enterprise carbon emissions. The stepwise regression method shows that the impact of digital inclusive finance on enterprise carbon emissions can be passed through effect of technological progress, environmental protection investment and financing constrain. This study has significant reference value for evaluating the impact of financial inclusion and policy implications in formulating differentiated strategies for achieving carbon emission reduction efficiency in enterprises.

[The current situation of occupational health in the Internet industry and countermeasures].

As an important force in promoting the transformation and upgrading of the national economy, the occupational health of the Internet industry's employees has received widespread attention. This paper examines the current situation of occupational health risks and management in the Internet industry at home and abroad, and on this basis reveals the physical and mental health problems of Internet industry employees. Combining the existing regulations, policies and standard documents at home and abroad, countermeasures are proposed to improve the relevant laws and regulations and their guidelines, implement relevant job design requirements, build a healthy working environment, optimise the work management system and carry out workplace health promotion, in order to provide ideas to accelerate the improvement of occupational health issues in the Internet industry.

Air Quality and Public Health Risk Assessment: A Case of an Industrial Area in Haridwar City, Uttarakhand (India).

BACKGROUND: Air pollution is a significant issue for a developing country like India and the air quality index (AQI) forecasting helps to predict air quality levels in advance and allows individuals to take precautionary measures to protect their health. OBJECTIVES: The study aimed to forecast the AQI for an industrial area (SIDCUL, Haridwar City) using a time series regression model. MATERIALS AND METHODS: Three years of existing AQI data points (post-COVID-19) were collected from the Uttarakhand Pollution Control Board for the SIDCUL area of Haridwar City and tried to know the status of AQI values for the following 12 months. Trend and seasonality components were seen through the decomposition process. Further, the augmented Dickey-Fuller test was applied to check the stationarity of the series before finalizing the best-suited time series model for forecasting the AQI values. RESULTS: With the help of autocorrelation function (ACF)/partial ACF plots, a seasonal autoregressive integrated moving average (ARIMA) (0,1,0) (1,0,0)[12] model was selected with the minimum akaike information criterion (253.143) and mean absolute percentage error (17.42%). The AQI values have also been forecasted for this industrial area (SIDCUL) for the following year. CONCLUSION: The seasonal ARIMA (0,1,0) (1,0,0)[12] model may be helpful to forecast the AQI values for a nonstationary time series dataset. Research indicates that the air of the SIDCUL area will become moderately polluted and may cause breathing discomfort to asthma patients' health. The scientists might apply this model to other polluted regions of the country so that the public and the government can take preventive measures in advance.

Chapitre 3. Identité décentralisée et biométrie dans l'automobile.

The car manufacturers continue their offer of mobility services around a customer who is no longer only owner of a vehicle but also simple temporary user. To improve the customer experience, we need to identify the real driver by using decentralized identity on the blockchain, coupled with a biometric system.In this article, based on the experience of a concrete project, we have evaluated the several biometrical methods for capturing information and their reliability in the automotive industry. We will share the lesson learned and the remaining tasks. This elegant means of identifying and exchanging data across customer journeys will open new opportunities between stakeholders. This collaborative co-creation will constitute a digital transformation in the interactions within an ecosystem.

Analysis of human capital effects introducing Bayesian quantile regression in the process of industrial structural upgrading.

In recent years, with the continuous evolution of the global economy and the adjustment of industrial structures, the understanding of the role played by human capital in the process of economic development has become particularly important. However, existing research on the impact of human capital on economic growth often adopts traditional regression methods, failing to comprehensively consider the heterogeneity and nonlinear relationships in the data. Therefore, to more accurately understand the influence of human capital on economic growth at different stages, this study employs Bayesian quantile regression method (BQRM). By incorporating BQRM, a better capture of the dynamic effects of human capital in the process of industrial structure upgrading is achieved, offering policymakers more targeted and effective policy recommendations to drive the economy towards a more sustainable direction. Additionally, the experiment also examines the impact of other key factors such as technological progress, capital investment, and labor market conditions on economic growth. These factors, combined with human capital, collectively promote the upgrading of industrial structure and the sustainable development of the economy. This study, by introducing BQRM, aims to fill the research gap regarding the impact of human capital on economic development during the industrial structural upgrading process. In the backdrop of the ongoing evolution of the global economy and adjustments in industrial structure, understanding the role of human capital in economic development becomes particularly crucial. To better comprehend the direct impact of human capital, the experiment collected macroeconomic data, including GDP, industrial structure, labor skills, and human capital, from different regions over the past 20 years. By establishing a dynamic panel data model, this study delves into the trends in the impact of human capital at various stages of industrial structure upgrading. The research findings indicate that during the high-speed growth phase, the contribution of human capital to GDP growth is 15.2% ± 2.1%, rising to 23.8% ± 3.4% during the period of industrial structure adjustment. Technological progress, capital investment, and labor market conditions also significantly influence economic growth at different stages. In terms of innovation improvement, this study pioneers the use of BQRM to gain a deeper understanding of the role of human capital in economic development, providing more targeted and effective policy recommendations. Ultimately, to promote sustainable economic development, the experiment proposes concrete and targeted policy recommendations, emphasizing government support in training and skill development. This study not only fills a research gap in the relevant field but also provides substantive references for decision-makers, driving the economy towards a more sustainable direction.

Performance and eye movement patterns of industrial design students reading sustainable design articles.

Sustainable design education plays a crucial role in cultivating sustainability awareness and competencies among students studying industrial design. This research investigates their sustainability levels, reading performance when engaging with articles, and fixation patterns during reading. 60 industrial design students participated in the study. We evaluated their sustainability levels using the Sustainable Consumption Measurement Scale. After reading both theoretical and case article, they completed tests assessing their recall and perspective scores. We collected eye-tracking data to analyze fixation duration and conducted lag sequential analysis on fixation transitions. Students were categorized into higher and lower sustainability groups based on their sustainability scores. Female students demonstrated higher sustainability levels, and students with design experience performed better in the higher sustainability group. While recall scores did not differ significantly, the higher sustainability group exhibited elevated perspective scores in theory article. Perspective scores were generally higher for case article compared to theory article. The higher sustainability group exhibited longer fixation durations in theory article, while the case article had longer fixation durations on images. Fixation transition patterns varied between theoretical and case article, with the former featuring transitions from images to texts, and the latter demonstrating transitions between images. This study provides valuable insights into sustainable design education for students studying industrial design.

Prevalence of Cardiovascular Disease (CAD) due to industrial air pollutants in the proximity of Islamabad Industrial Estate (IEI), Pakistan.

Contaminated air quality, in lieu of massive industrial pollution, is severely attributing to health anomalies in the proximity of industrial units. Cardiovascular Disease (CAD) is rising around industrial units in the planned capital city of Pakistan, Pakistan. To study self-reported CAD in the proximity of Industrial Estate Islamabad (IEI) by equating two distinct study groups as 'Band-I': the residence 0-650 meters and 'Band-II' 650-1300 meters radius around the perimeter of IEI. The perimeters were digitized using Google Earth and GIS. Field survey was conducted on deploying 388 (194 in each Band) close-ended (self-administered) questionnaires at the household level, after adjusting the potential confounding variables. The research calculated odds ratios (ORs) of the CAD at 95% CI. The study's findings of the multiple logistic regression for ORs confirmed a significant increase in CAD problems due to industrial affluents in Band-I than in Band-II which were less severe and less life-threatening. Study confirmed high incidences of high blood pressure and breathing issues (up to 67%), due to accumulation of unhealthy affluents thus leading to heart stroke (Band I = 56.20% and Band II = 60.30%). It is aided by smoking that has increased CAD in Band-I. Societal attributes of knowledge, beliefs, attitudes, and preferences fail to safeguard the local residents amid high concentration of harmful pollutants. As a counter measure the affected respondents engaged in highlighting the issue to the concerned public offices, yet there is a high need on part of the capital government to take mitigative measures to immediately halt the disastrous industrial air emissions to save precious lives.

Senior executive characteristics: Impact on ESG practices and corporate valuation relationship.

In recent years, sustainable development and green growth and performance of companies in environmental, social, and corporate governance (ESG) has received widespread attention from all sectors of society. Based on panel data of A-share listed companies in China from 2009 to 2022, this study employs a two-way fixed effects model to explore the mechanism of the relationship between ESG practices and corporate value, as well as the moderating effect of executive characteristics within this relationship. The results indicate a robust positive relationship between ESG practices and corporate value. However, this relationship is moderated by the academic backgrounds of senior executives, who negatively influence it, and by male executives, who exert a positive moderating effect. Furthermore, this study reveals the variable impacts of ESG practices in different corporate settings, industries, and institutional frameworks. Moreover, it demonstrates how ESG practices boost corporate value through an enhanced reputation and increased government innovation subsidies. It offers new insights on the strategic value of ESG for corporations and policymakers. It also extends the theoretical framework by integrating attention-based and upper echelons perspectives into the ESG discourse. .

The predictive capability of several anthropometric indices for identifying the risk of metabolic syndrome and its components among industrial workers.

Metabolic syndrome (MetS) is closely associated with adverse cardiometabolic outcomes. The objective of this study was to identify practical methods that could enable the effective identification of MetS based on anthropometric indices. The basis of our study involved retrospective database obtained from routine medical prophylactic examinations. This was a cross-sectional study on the health status of male workers employed in hazardous working conditions at industrial enterprises in the Ural region conducted in 2019. A total of 347 male workers employed under hazardous working conditions were investigated. The presence of MetS was established by a healthcare professional in accordance with the guidelines of the International Diabetes Federation (IDF). Simple linear regression was used to evaluate the associations between anthropometric indices and MetS incidence. Logistic regression was used to determine the odds ratios of MetS in relation to increases in anthropometric indices. ROC curves were calculated to compare the ability of each anthropometric index to predict MetS and to determine the diagnostic thresholds of the indicators considered. According to the IDF criteria, 36.3% of the workers had MetS. A direct relationship was found between the individual components of MetS and the anthropometric indices studied. The highest OR was shown by the Body Roundness Index (BRI) of 2.235 (95% CI 1.796-2.781). For different age quartiles, the optimal cut-off values for predicting MetS were as follows: BRI, 4.1-4.4 r.u.; body shape index (ABSI), 0.080-0.083 m11/6 kg-2/3; and lipid accumulation product (LAP), 49.7-70.5 cm mmol/l. The most significant associations with MetS were observed where the values were greater than these cut-off points (Se = 97.4%). The results of this study demonstrated the rapid use of new anthropometric indicators, which have shown good predictive ability and are quite easy to use.

Impact of digital technology innovation on carbon intensity: evidence from China's manufacturing A-share listed enterprises.

Current studies do not provide a consensus on whether digital technology innovation can reduce enterprise carbon intensity despite the rise of the digital economy. This paper examines the role and influence pathway of digital technology innovation on enterprise carbon intensity using data from A-share listed enterprises in China's manufacturing industry from 2012 to 2021. The findings indicate that (1) digital technology innovation has been found to significantly reduce enterprise carbon intensity, as confirmed by numerous robustness and endogeneity tests. However, its inhibitory effect on carbon intensity shows a marginal decreasing trend. (2) In the heterogeneity analysis, it was found that digital technology innovation significantly reduces the carbon intensity of consuming coal, coke, kerosene, and diesel. From various perspectives, including enterprise, industry, and external environment, there are significant differences in the carbon reduction effects of digital technology innovation. (3) The analysis of impact paths reveals that digital technology innovation can affect enterprise carbon intensity through three paths: improving productivity, enhancing green innovation efficiency, and adjusting energy consumption. (4) Upon further analysis, it was discovered that the spillover effect of digital technology innovation is more pronounced in the industry cohort of enterprises. Additionally, digital technology innovation plays a positive role in enhancing enterprise ESG performance. The paper's findings offer empirical evidence and decision-making references for the government to develop reasonable policies for reducing carbon emissions, promoting green and low-carbon enterprise transformation, and actively and steadily achieving the goal of carbon peaking and carbon neutrality.

Inter-provincial embodied carbon emission space and industrial transfer paths in China.

To bolster the dual-circulation development model and green economy, this study delves into the spatiotemporal dynamics of implied carbon transfer in China's inter-provincial and inter-industrial trade, emphasizing its significance for the "dual carbon" objectives. Utilizing multi-regional input-output data from 2012, 2015, and 2017, we employed the multi-region input-output model to gauge embodied carbon transfers across 31 provinces and 28 industries. The Structural Decomposition Analysis (SDA) model further decomposed the growth of trade-related carbon emissions. Key findings include: (1) The electricity and thermal power sectors dominate carbon transfers, with secondary industries seeing rapid growth; (2) Northern provinces significantly outweigh southern ones in carbon transfers and the main direction of it is towards affluent southern coastal regions; (3) Scale effect plays a pivotal role in these transfers. Conclusively, it is crucial for regulatory authorities to rationally formulate region-specific emission policies for inter-regional coordination, and future studies can focus on industrial and spatial clustering effects.

Digital financial inclusion, industrial structure and urban-Rural income disparity: Evidence from Zhejiang Province, China.

Rising income inequality challenges economic and social stability in developing countries. For China, the fastest-growing global digital economy, it could be an effective tool to promote inclusive development, narrowing urban-rural income disparity. It investigates the role of digital financial inclusion (DFI) in narrowing the urban-rural income gap. The study uses panel data from 52 counties in Zhejiang Province, China, from 2014 to 2020. The results show that the development of DFI significantly reduces rural-urban and rural income inequality. The development of DFI helps optimize industrial structure and upgrade the internal structure of agriculture, facilitating income growth for people in rural areas. Such effects are greater in poorer counties. Our findings provide insights into why rapid DFI and the narrowing of the rural-urban income disparity exist in China. Moreover, our results provide clear policy implications on how to reduce the disparity. The most compelling suggestion is that promoting the optimization of industrial structure through DFI is crucial for narrowing the urban-rural income gap.

The role of trophic, mutualistic, and competitive interactions in an industrial symbiosis process implementation: an ecological network perspective.

For both government and private institutions, the development of collaboration networks becomes an element of great importance for the implementation of related policies such as the circular economy and sustainable practices in manufacturing. Despite the above, such initiatives have not received as much attention in literature but have been decisive as both public and private initiatives. Initiatives in Latin America do not escape this scenario, especially in the creation of conditions that allow the promotion of approaches such as industrial symbiosis. In this way, the present research is aimed at identifying the role of trophic, mutualistic, and competitive interactions in an industrial symbiosis process implementation. A network analysis model is used to achieve this purpose. This technique allows us to know the degree of importance of the different actors that are part of a network, as well as the factors that determine the implementation of initiatives such as industrial symbiosis. Among the results are that empirical findings confirm the presence of trophic interactions that enhance resource efficiency, mutualistic interactions fostering collaboration and synergy, and competitive interactions promoting efficiency and dynamism. Additionally, a green culture, business size, and innovation activities are revealed as influential factors amplifying network dynamics.

The impact of environmental regulations on the green development of the mariculture industry: empirical analysis based on provincial panel data in coastal areas of China.

With the continuous increase in global mariculture production and aquaculture areas, the environmental pollution caused by the mariculture industry is becoming increasingly serious. Faced with environmental issues, countries worldwide have formulated environmental regulations to scientifically intervene in marine environmental pollution issues and promote the green development of the mariculture industry. However, we must determine if strict environmental regulations can effectively promote the green development of the mariculture industry. This article uses the inter-provincial panel data of China's coastal areas from 2003 to 2019 as a sample. We use the entropy-technique for order of preference by similarity to ideal solution method to measure the intensity of environmental regulation in China's coastal areas and the level of green development of the mariculture industry. On this basis, an economic geography nested matrix was selected to construct a spatial panel econometric model to empirically explore the impact of environmental regulations on the green development of the mariculture industry. This approach also allows us to examine the heterogeneity of the impact of different types of environmental regulations on the green development of the mariculture industry. The research results indicate that environmental regulations have a "U-shaped" impact on the green development of the local mariculture industry, while they have an inverted "U-shaped" impact on the green development of the nearby mariculture industry. Furthermore, heterogeneity exists in the impact of different types of environmental regulations on the green development of the mariculture industry. Based on the research results, this article proposes policy recommendations from the perspectives of flexibly adjusting the intensity of environmental regulations, accelerating the development of voluntary-based environmental regulations, and regulating competition among local governments, which can provide decision-making references for the government to adjust environmental regulation policies and improve the level of green development in the mariculture industry.

Breaking the spiral of silence: News and social media dynamics on sexual abuse scandal in the Japanese entertainment industry.

Highlighting minorities and crime survivors through public discourse is essential for their support and protection. However, advocating for minorities is challenging due to the fear of potential isolation from one's social circles. This reluctance contributes to the societal phenomenon known as the "spiral of silence," significantly impeding efforts to support socially vulnerable individuals. This study centers on a pivotal instance where the silence surrounding sexual abuse in the Japanese entertainment industry was disrupted, in which the late company president had allegedly abused idol trainees of the company for decades. Utilizing extensive data from news media and social media, the study probes the engagement dynamics of public attention to this scandal. Results indicate that users on social media provided earlier and greater coverage for this scandal compared to news media outlets. Furthermore, television demonstrated a significant delay in addressing this issue compared to other news media, such as tabloids, magazines, and online news. Regarding social media engagement, idol fans exhibited a more subdued response to the issue compared to the general public. Notably, fans more loyal to the company tended to be slower to mention the issue, with a higher likelihood of standing in defense of the perpetrators. Moreover, conflicting attitudes were observed within the fan communities, culminating in an observable "echo chamber" phenomenon. This paper presents a novel examination of the process of disruption of social silence and offers critical insights for aiding vulnerable individuals in environments dominated by an unacknowledged spiral of silence. This study is novel in that it suggests a reinterpretation of the "spiral of silence theory" in the age of social media, through a comprehensive analysis of relevant social media data and news media data. This contributes to the body of research that has analyzed the spiral of silence theory online.

Utilization of foreign investment in the productive service industry in Hubei province, China and its optimization counter-measures.

The Global Investment Report 2023 revealed that after a sharp decline in 2020 and a strong rebound in 2021, global foreign direct investment (FDI) declined by 12 percent to $1.3 trillion in 2022. However, in developing countries, FDI increased by 4% to $916 billion, a record share of more than 70% of global flows. The number of greenfield investment projects in developing countries increased by 37 percent and international project finance transactions by 5 percent. Foreign investment from China, the second largest recipient of foreign investment globally, increased by 5 percent. The service industry has become the mainstream industry in the global FDI structure. The global industry is accelerating its transformation to a "service-based economy," international FDI in productive service industries has become an essential means of industrial transfer in developed countries and a meaningful way to upgrade the industrial structure and high-quality development in emerging economies. As a representative province in central China, Hubei Province has unique advantages in human capital, factor cost, and market potential, which provide preferential conditions to attract foreign investment. This paper first introduced the concept of the productive service industry, based on the relevant statistical data from 2011 to 2022, focused on the current situation of foreign investment utilization in five major sub-sectors of the productive service industry in Hubei Province in the past ten years, and empirically investigated the impact of foreign investment utilization in five major sub-sectors of the productive service industry on the economic growth of Hubei Province, and obtained that the level of foreign investment attraction varied significantly among the regions in Hubei Province. The three productive service industries, namely transportation, storage and postal services, information transmission, software and information technology services, and financial services, played a significant role in the active attraction and optimal utilization of foreign capital and the economic development of Hubei Province. Based on this, it was proposed to build a market-oriented rule of law and internationalized business environment, improve the infrastructure construction in different regions of the province, focus on the training of professional talents for the development of productive service industries, and pay attention to the improvement of independent innovation capacity.

Advances in 2D Materials Based Gas Sensors for Industrial Machine Olfactory Applications.

The escalating development and improvement of gas sensing ability in industrial equipment, or "machine olfactory", propels the evolution of gas sensors toward enhanced sensitivity, selectivity, stability, power efficiency, cost-effectiveness, and longevity. Two-dimensional (2D) materials, distinguished by their atomic-thin profile, expansive specific surface area, remarkable mechanical strength, and surface tunability, hold significant potential for addressing the intricate challenges in gas sensing. However, a comprehensive review of 2D materials-based gas sensors for specific industrial applications is absent. This review delves into the recent advances in this field and highlights the potential applications in industrial machine olfaction. The main content encompasses industrial scenario characteristics, fundamental classification, enhancement methods, underlying mechanisms, and diverse gas sensing applications. Additionally, the challenges associated with transitioning 2D material gas sensors from laboratory development to industrialization and commercialization are addressed, and future-looking viewpoints on the evolution of next-generation intelligent gas sensory systems in the industrial sector are prospected.

Industry star or production elite: evidence from total factor productivity of Chinese electricity sector's green transformation.

China is constantly seeking rapid, high-quality growth in order to meet its carbon peaking and neutrality goals. Approximately 40% of China's carbon emissions come from the electric power industry, which is beset by issues of poor efficiency and excessive emissions. Thus, it is essential to determine if environmental restrictions increase economic benefits total factor productivity while still preserving the environment. We use the Quasi-DID method to examine the impact of carbon emissions trading scheme on firm-level total factor productivity of electric power companies. The findings demonstrate the following: (1) carbon emissions trading scheme considerably impedes total factor productivity development; (2) the primary cause of this detrimental impact is the need for additional improvements in marketization since green innovation is still in its infancy; (3) additional study indicates that law enforcement's heterogeneity is what affects this restriction. Our research may both enhance the Chinese carbon emissions trading scheme's effectiveness assessment framework and point out several potential avenues for high-quality growth.

An investigation of antecedents and consequences of green value internalisation among sampled UK enterprises.

Despite the growing popularity of the concept of green value internalisation, research on how this concept is being accomplished at the enterprise level is still limited. The purpose of this study is to address this knowledge gap by drawing from previously known concepts of green value and value internalisation. It examines the antecedents and consequences of green value internalisation and evaluates how these environment-leaning approaches impact competitive advantage. This study uses the resource-based view and the stakeholder theory as theoretical lenses in linking green value internalisation to its antecedents and how these impact competitive advantage. A two-step approach involving a measurement model and a structural model was used to analyse survey data from 213 UK enterprises to validate the research hypotheses. Hypotheses testing shows that green value internalisation has a positive and significant impact on green criteria development. The results also show that external pressure positively and significantly affects green value internalisation. These findings extend prior knowledge by establishing the level of significance in the relationship among the antecedents and consequences in the research model. The research design for this study draws from a systematic literature review. The study offers rigorous empirical insights for implementing green value internalisation as a value-creating strategy. However, the antecedents and consequences examined in this study may not capture in detail all underlying constructs. Hence future studies should proffer valid and reliable instruments for these constructs. The findings provide managers from enterprises across a broad industry size range seeking to implement green value internalisation with resources for embedding an enterprise-level pro-environmental strategy.