941 research outputs found
Impact of human capital on endogenous power - evidence from agriculture-oriented town development projects across China
No full textWith the continuous adoption of digital and information technologies in the agriculture sector, the level of modernization and digital transformation of agriculture is improving, which raises new requirements on education level, professional skills, and management experience of agricultural workers. There is now an inevitable trend of professionalization of agricultural production and farmers’ personal development, and a pressing need to comprehensively evaluate human capital beyond population and age distribution, extending to cover education, qualification, professional experience, and more.Our research takes a strategic perspective to investigate issues encountered in agriculture-oriented town development projects and “rural revitalization” practice, incorporating human capital theory, scale economy theory, endogenous economic growth theory, and growth pole theory. We firstly develop a theoretical framework for the impact of human capital on the endogenous driving forces in agriculture-oriented town projects through a comprehensive literature review and secondary data. Screening data at the national level (including those projects approved by the Ministry of Housing and Urban-Rural Development and other authorities), 76 agriculture-oriented towns are selected for panel data collection and core variable measurements (from 2017 to 2022). A fixed effect model is employed to examine how the three dimensions of human capital (i.e., years of education, vocational training, work experience) affect the endogenous power.Secondly, we empirically test the mediation effect of mechanism variables (such as agricultural industrial structure optimization, agricultural organization, and agricultural mechanization) between human capital and the endogenous driving forces of agricultural characteristic towns, and the moderator variables including technological innovation and application, and digitalization and digital transformation in agriculture. Thirdly, we adopt a panel threshold effect model to further explore two specific dimensions of human capital, namely average years of education and vocational training.Fourthly, gradual test method and Sobel method are applied to empirically test the mediation effect of mechanism variables such as agricultural industrial structure optimization, agricultural organization, and agricultural mechanization on the three dimensions of human capital and the endogenous driving forces, as well as the heterogeneity of this mediation effect across the three major regions of China (i.e., the eastern, the central, and the western). Finally, we empirically test the moderating effects of technological innovation and application, and digitalization and digital transformation level on the relationship between the three dimensions of human capital and the endogenous driving forces of agriculture-oriented towns. The main findings of this book are as follows:(1) The three dimensions of human capital in agriculture-oriented towns are on the rise, yet there are differences across regions and supply chain functions. Firstly, overall, the average years of education for agricultural workers have increased, at a decreasing scale from Eastern, to Central, to Western China, while at increasing levels from agricultural planting, agricultural service, to agricultural product processing. Secondly, the degree of vocational training for agricultural workers is overall enhanced, with the eastern region generally higher than the central and western regions. Regarding their supply chain functions, processing-focused towns have the highest level of training, followed by service-focused towns. Thirdly, such heterogeneity is also observed in labor’s work experiences.(2) We propose a comprehensive evaluation model with 13 indicators and the entropy method and principal component analysis method. The measured values show an overall increase over the six-year period. Regionally, the decline in the eastern, central, and western regions continued from 2017 to 2019; since 2020, it is high in the western and low in the central. The measured values of endogenous driving forces and the three dimensions of human capital present a linear relationship.(3) Direct mechanism test. All three dimensions of human capital have a significant promoting effect on the endogenous driving forces of agriculture-oriented towns. Firstly, the average years of education has the most significant impact in central region, followed by the western and eastern regions. The impact coefficients decrease successively in western, central, and eastern regions they, and increase successively in agricultural product processing, service, and planting and breeding. Secondly, vocational training has a significant positive impact on endogenous driving forces in the western region, but not in other regions; it also has a significant positive impact on planting and breeding, but no significant impact in service and processing. Thirdly, work experience has a significant positive impact on endogenous driving forces in both central and western regions, but not in eastern region; it has the most significant impact on planting and breeding, then service, while agricultural product processing-focused towns do not pass the significant standard test. The threshold effect test reveals: Firstly, there is a single threshold effect of the average years of education on the endogenous driving forces of agriculture-oriented towns in overall, central, and planting and service-focused town regions, and the positive driving effect of education level on endogenous driving forces shows a marginal decreasing trend as the average years of education of agricultural workers increase. Secondly, there is a single threshold effect of vocational training on the endogenous driving forces in overall, eastern, western, and planting and breeding agriculture-oriented towns. When the threshold value is exceeded, the impact of vocational training on endogenous driving forces shows a marginal increasing trend.(4) Mechanism test. Mechanism variables such as agricultural industrial structure optimization, agricultural organization, and agricultural mechanization play a significant mediation role for the impact of human capital on the endogenous driving forces in agriculture-oriented towns, and exhibit heterogeneity across regions and business foci. Firstly, industrialization and digital transformation of the agriculture industry play a positive mediation role in the relationship between average years of education and vocational training and the growth of endogenous driving forces, while it has a significant masking effect on the relationship between work experience and the growth of endogenous driving forces. Secondly, scaling up of agriculture plays a partial mediation role in the mechanism of actions between average years of education, vocational training, and the endogenous driving forces; it plays a full mediation role in the mechanism of action between work experience and the endogenous driving force of agricultural characteristic towns. Thirdly, agricultural mechanization plays a partial mediation role in the mechanism of action between average years of education and vocational training of agricultural workers and the endogenous driving forces; it has a masking effect on the mechanism of action between work experience and the endogenous driving forces.(5) Regression analysis. Technological innovation, and digitalization and digital transformation in the agriculture sector have significant moderation effects on the relationship between human capital and the internal driving forces of agriculture-oriented towns. They play different moderation roles in the relationship between average years of education, vocational training, and work experience and the internal driving forces of agricultural characteristic towns, and there are differences in the direction and significance of the moderating effects between regions and business foci.(6) Based on the above analyses and findings, policy recommendations are made for coordinated development of agricultural human capital and the endogenous. Firstly, improve the quality of public services and attract high-quality talents to return to town and rural regions. Secondly, improve the education system, as the quality of secondary school education is the cornerstone for attracting high-quality talents to return to characteristic towns. Thirdly, improve the agricultural career development through vocational training, enhancing quality control and assessment, and enable tailored training approaches. Finally, establish an agricultural human capital development scheme, and allow capable individuals to make a difference
Replication Data for: CESM (version 1.2.2.1) Simulated 2-m Air Temperature and Precipitation (Sun and Wang 2019)
No full textCESM (version 1.2.2.1) simulated 2-m air temperature and precipitation analyzed in Sun and Wang (2019
Replication Data for: CESM (version 1.2.2.1) Simulated 2-m Air Temperature and Precipitation (Sun and Wang 2019)
No full textCESM (version 1.2.2.1) simulated 2-m air temperature and precipitation analyzed in Sun and Wang (2019
ACR878360 Supplemental Material - Supplemental material for Altered brain structural and cognitive impairment in end-stage renal disease patients with secondary hyperparathyroidism
No full textSupplemental material, ACR878360 Supplemental Material for Altered brain structural and cognitive impairment in end-stage renal disease patients with secondary hyperparathyroidism by Xijun Gong, Liwei Zou, Hanqiu Wu, Yanqi Shan, Guiling Liu, Suisheng Zheng and Longsheng Wang in Acta Radiologica</p
Vegetation dynamics in the climate of West Africa
No full textThesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2000.Includes bibliographical references (p. 211-224).The climate of West Africa exhibits significant variability at the time scale of decades. The persistent drought of the past three decades is an example of such variability. This study investigates the role of vegetation dynamics in shaping the low-frequency variability of the climate over West Africa. A zonally symmetric, synchronously coupled biosphere-atmosphere model (ZonalBAM) which includes explicit representation of vegetation dynamics has been developed, and has been validated using observations on both the atmospheric and biospheric climate. The model is then used to study the dynamics of the coupled biosphere-atmosphere system over West Africa. Based on the model sensitivity to initial conditions and the resilience of the coupled system with respect to perturbations, we demonstrate that the coupled biosphere-atmosphere system over West Africa has multiple equilibrium states, with reversible transitions between different equilibria. The two-way biosphere-atmosphere feedback is a significant process in both climate persistence and climate transition. Based on long-term climate simulations using ZonalBAM driven with the observed sea surface temperature (SST) variations, our study shows that vegetation dynamics is a significant process in shaping the climate variability of West Africa. The response of the regional climate system to large-scale forcings is significantly regulated by vegetation dynamics. The relatively slow response of vegetation to changes in the atmosphere is a significant mechanism that acts to enhance the low-frequency rainfall variability. Climate transitions between different equilibria act as another mechanism contributing to the low-frequency rainfall variability - multi-decadal fluctuations can take place as a collective reflection of climate persistence at one equilibrium and climate transition towards another. Vegetation dynamics seems to play an important role in the development and persistence of the current Sahel drought. The most likely scenario for the triggering mechanism of the Sahel drought would involve a combination of several processes including regional changes in land cover as well as changes in the patterns of global and regional SST distributions. However, regardless of the nature of the triggering mechanism, the response of the natural vegetation to the atmospheric changes is the critical process in the development and persistence of the observed drought.by Guiling Wang.Ph.D
A framework for use of wireless sensor networks in forest fire detection and monitoring
No full textForest fires are one of the main causes of environmental degradation nowadays. Current surveillance systems for forest fires lack in supporting real-time monitoring of every point of a region at all times and early detection of fire threats. Solutions using wireless sensor networks, on the other hand, can gather sensory data values, such as temperature and humidity, from all points of a field continuously, day and night, and, provide fresh and accurate data to the fire-fighting center quickly. However, sensor networks face serious obstacles like limited energy resources and high vulnerability to harsh environmental conditions, that have to be considered carefully. In this paper, we propose a comprehensive framework for the use of wireless sensor networks for forest fire detection and monitoring. Our framework includes proposals for the wireless sensor network architecture, sensor deployment scheme, and clustering and communication protocols. The aim of the framework is to detect a fire threat as early as possible and yet consider the energy consumption of the sensor nodes and the environmental conditions that may affect the required activity level of the network. We implemented a simulator to validate and evaluate our proposed framework. Through extensive simulation experiments, we show that our framework can provide fast reaction to forest fires while also consuming energy efficiently
Exploring the relation between gender politics and representative government in the Maghreb: analytical and empirical observations
No full textThis thesis uses analytical and empirical methods to explore the relation between gender standards and democratic standards in the Maghreb, which includes Algeria, Morocco, and Tunisia. The analytical approach consists of considering theories that link gender standards and democratic standards, and analyzing whether and to what extent such theories would apply or not apply to the Maghreb. The empirical approach consists of taking measurements that reflect gender standards and democratic standards across the three countries and four different milestones of their recent history (1970, 1980, 1990, 2000), and applying statistical methods to compute correlations and regressions. Because the empirical approach yields no significant correlation between gender standards and democratic standards in the Maghreb, I analyze this statistical correlation for other sets of countries that are part of Maghrebian identity: Arab countries, Muslim countries, African countries, and Mediterranean countries. The combined results of these analyses give us some insight into possible explanations of the empirical observations.Ph.D.Includes bibliographical references (p. 261-275)by Amel Mil
Mobile intelligence analytics for urban smart living
No full textToday, as the sensing technology and mobile computing have been popularized, a variety of mobile data related to human mobility and urban geography have been accumulated in a large amount. This type of data comprehensively records the fine-grain events of our cities through “4W” aspects of information: What happened? Where it happened? When it happened? And who did it? By proper analysis, this data can be a rich source of mobile intelligence to support various location-based and real-time decision-making solutions for a broad range of urban smart living applications. Indeed, mobile intelligence analytics plays an important role in urban life because city residents often make choices under more uncertainty and can benefit more from personalized advice based on their preferences and contexts. Therefore, it is especially meaningful to develop data-driven methodologies which can effectively and efficiently guide users to make optimal decisions to achieve the goal of urban smart living. In this dissertation, we aim to address the unique challenges of urban smart living in mobile and pervasive business environments from both theoretical and practical perspectives. Specifically, we first develop a safety-aware house ranking system by considering the impact of neighborhood criminal offenses on house values. The proposed framework extracts features regarding community safety conditions of different houses, and utilizes multiply safety features to rank houses by unit value. To enhance safety-aware ranking, we introduce major characteristics of house profile to control the similarity between houses during pair-wise ranker learning. The experimental results show that the proposed method substantially outperforms the baseline learn-to-rank methods for safety-aware house ranking. Moreover, in the second study, we introduce an effective point-of-interest (POI) recommender system to consider the temporal compatibility between POI popularity and user regularity. We propose to use the massive human mobility data to profile the temporal pattern of POI popularity, and infer the regularity pattern of users based on the POI they visited through a modeling intuition ``you are where you go". We demonstrate the effectiveness of the proposed model through the extensive experiments on the real-world datasets of New York City. Finally, we introduce a zone embedding framework to identify the urban functions of city zones by studying massive origin-destination transportation data. We focus on exploiting the idea of word embedding in natural language processing domain to learn zone functions in urban computing domain by developing a novel analog from word co-occurrence to zone co-occurrence using human mobility patterns. To incorporate the contexts of human mobility in our framework, we develop the directed and temporal co-occurrence for considering mobility direction and time, and the different importance of co-occurrence for considering travel distance and zone attractiveness. The evaluation validates the proposed method and shows that the learned embeddings can comprehensively capture the urban functions of city zones. From the three studies, we conclude that mobile intelligence analytics can be powerful at disclosing patterns, relations and hidden knowledge, and it is promising to explore the power of mobile intelligence to provide location-based insights, and ultimately, to improve business performance.Ph.D.Includes bibliographical referencesby Zijun Ya
From data to dynamism: the role of data and learning models in startup potential analysis
No full textIn the contemporary era, the landscape of innovation and entrepreneurship is dynamically evolving, fueled by a substantial surge in venture capital investments and the rapid expansion of the global startup ecosystem. This burgeoning growth not only highlights the vibrant nature of modern economies but also brings to the forefront the critical importance of identifying startups with high potential for success. As venture capital firms and investors seek to maximize their returns on investment, the ability to accurately assess and predict the future performance of these nascent companies becomes paramount. This dissertation delves into the heart of this challenge, aiming to refine and enhance the methodologies used in evaluating startup potential, thereby contributing valuable insights and tools to both academic scholars and industry practitioners.
Existing methods for assessing startup potential have predominantly relied on static variables such as financial performance indicators, market size estimates, and competitive positioning. While these factors offer valuable insights, they fall short in capturing the dynamic and often unpredictable nature of startup growth and success. This raises several pertinent questions: How can we move beyond these traditional metrics to more accurately predict startup success? Furthermore, is it possible to develop more advanced tools that not only provide predictions but also facilitate a more interactive, dynamic evaluation process? These questions highlight the limitations of current approaches and pave the way for the innovative research presented in this dissertation, which seeks to explore these opportunities through the application of advanced data analytics and learning models.
The dissertation is structured around three main chapters, each contributing to the overarching aim of developing a comprehensive framework for startup evaluation. The first chapter emphasizes the importance of mapping the interactions between various entities within the startup ecosystem, including companies, venture capital firms, and individuals. This interaction-centric view provides a foundational understanding of the complex interdependencies that influence startup success.
Building on this foundation, the second chapter introduces an expanded interaction network and integrates company demographic features to improve the identification of high-potential startups. Additionally, this chapter explores the entrepreneurial homophily principle, which posits that startups with similar characteristics tend to cluster together, further supporting the theoretical underpinnings of the proposed methodologies.
The third chapter represents a pioneering effort to leverage large language models (LLMs) for building an interactive, domain-centric tool aiming at dynamically evaluating startup potential. This novel application of LLMs opens up exciting possibilities for creating an interactive agent that can continuously update its assessments based on evolving data, offering a more fluid and responsive tool for venture capital decision-making.
In summary, this dissertation marks a significant advancement in the field of startup evaluation by utilizing a diverse array of entrepreneurial data, combined with cutting-edge learning models. The research not only advances our theoretical understanding of startup dynamics but also offers practical tools for identifying startups with the highest potential for success. Through its comprehensive analysis and innovative methodologies, this work stands as a seminal contribution to the ongoing efforts to enhance the precision and relevance of startup potential assessment.Ph.D.Includes bibliographical reference
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