AGGLOMERATION ECONOMIES, INVESTMENT IN EDUCATION, AND REGIONAL DEVELOPMENT

This dissertation consists of two essays that study the linkages among agglomeration economies, investment in education, and regional development. In the first essay, I study the impact of a federal educational investment on various aspects of local economies. In the second essay, I examine the spillover effects among workers with different skills, which are identified by their college majors. The first essay presents evidence of direct spillovers from universities and examines the short- and long-run effects of university activities on geographic clustering of economic activity, labor market composition and local productivity. I treat the designation of land-grant universities as a natural experiment after controlling for the confounding factors with a combination of synthetic control methods and event-study analyses. Three key results are obtained. First, the designation substantially increased local population density. Second, the share of manufacturing workers in the population, an indicator of labor market composition, was not affected by the designation. Third, the designation greatly enhanced local manufacturing productivity, as measured by local manufacturing output per worker, especially in the long run. This positive effect on the productivity in non-education sectors suggests the existence of spillovers from universities. Over an 80-year horizon, I estimate that most of the increase in manufacturing productivity was because of direct spillovers from universities instead of induced agglomeration economies that arise from the increase in population. The second essay studies the manner and extent to which worker skill type affects agglomeration economies that contribute to productivity in cities. I use college major to proxy for skill type among workers with a Bachelor\u27s degree. Workers with college training in information-oriented and technical fields (e.g. STEM areas such as Engineering, Physical Sciences, and Economics) are associated with economically important within-field agglomeration economies and also generate sizeable spillovers for workers in other fields. In contrast to related work by Florida (2002a, 2002b), within-field and across-field spillovers for workers with college training in the arts and humanities are much smaller and often non-existent. While previous research suggests proximity to college-educated workers enhances productivity, these findings suggest that not all college educated workers are alike. Instead, positive spillover effects appear to derive mostly from proximity to workers with training in information-oriented and technical fields

What is valued most by patients with type 2 diabetes mellitus when selecting second-line antihyperglycemic medications in China

Objective: To estimate patient preferences for second-line antihyperglycemic medications in China. Methods: A face to face survey with the best-worst scaling (BWS) choices was administered in patients with diagnosed type 2 diabetes mellitus (T2DM). Study participants were asked to indicate which attribute they valued most and which attribute they valued least in 11 choice sets, each of which consisted of five alternatives out of 11 antihyperglycemic medication-specific attributes (treatment efficacy, weight change, hypoglycemic events, gastrointestinal side effects, cardiovascular health, urinary tract infection and genital infection side effects, edema, mode of administration, bone fracture, dosing frequency and out-of-pocket cost). A counting approach, a conditional logit model, and K-means clustering were used to estimate the relative importance of items and preference heterogeneity. Results: A total of 362 participants were included with a mean age of 63.6 (standard deviation: 11.8) years. There were 56.4% of participants were women, and 56.3% being diagnosed with diabetes for at least 5 years. Efficacy, cardiovascular health and hypoglycemic events were valued most, while dosing frequency, mode of administration and bone fracture were valued least. The K-means clustering further showed preference heterogeneity in out-of-pocket cost across the participants. Conclusion: Our study suggests that treatment efficacy, cardiovascular health and hypoglycemic events are valued most by Chinese patients with T2DM when selecting second-line antihyperglycemic medications. The study improves the understanding of patients’ preferences for second-line antihyperglycemic medications in China

Experimental Study on Hygrothermal Deformation of External Thermal Insulation Cladding Systems with Glazed Hollow Bead

This research analyzes the thermal and strain behavior of external thermal insulation cladding systems (ETICS) with Glazed Hollow Beads (GHB) thermal insulation mortar under hygrothermal cycles weather test in order to measure its durability under extreme weather (i.e., sunlight and rain). Thermometers and strain gauges are placed into different wall layers to gather thermal and strain data and another instrument measures the crack dimensions after every 4 cycles. The results showed that the finishing coat shrank at early stage (elastic deformation) and then the finishing coat tends to expand and become damaged at later stage (plastic deformation). The deformation of insulation layer is similar to that of the finishing coat but its variation amplitude is smaller. Deformation of substrate expanded with heat and contracted with cold due to the small temperature variation. The length and width of cracks on the finishing coat grew as the experiment progressed but with a decreasing growth rate and the cracks stopped growing around 70 cycles

Job preferences of undergraduate nursing students in eastern China: a discrete choice experiment

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were madeBackground Shortage and mal-distribution of nursing human resources is an intractable problem in China. There is an urgent need to explore the job preferences of undergraduate nursing students. The main aim of this study is to investigate the stated preferences of nursing students when choosing a job. Methods A discrete choice experiment (DCE) was conducted to assess job preferences of the final year undergraduate nursing students from four medical universities/colleges in Shandong Province, China. Job attributes include location, monthly income, bianzhi (which refers to the established posts and can be loosely regarded as state administrative staffing), career development and training opportunity, work environment and working strength. Mixed logit models were used to analyze the DCE data. Results A total of 445 undergraduate nursing students were included in the main DCE analysis. They demonstrated higher preference for a job with higher monthly income, and the probability of choosing a rural job would increase to 92.8% if monthly income increased from RMB 2000 (US$296) to RMB 8000 (US$ 1183). They expressed higher stated preferences for a job which required light working strength and with excellent work environment over other non-economic attributes. Among all attributes, location was the least important attribute. Subgroup analysis showed that students who came from city or county and whose family income was more than RMB 50 000 (US$ 7396) were significantly willing to pay more monthly income for a job in city. Conclusions This study confirmed that economic and non-economic factors both affected the job choices of the students. These results may be more effective for policymakers to perfect the employment policies and design strategies to attract more nursing students taking jobs in rural areas

Multi-source adversarial transfer learning for ultrasound image segmentation with limited similarity

Lesion segmentation of ultrasound medical images based on deep learning techniques is a widely used method for diagnosing diseases. Although there is a large amount of ultrasound image data in medical centers and other places, labeled ultrasound datasets are a scarce resource, and it is likely that no datasets are available for new tissues/organs. Transfer learning provides the possibility to solve this problem, but there are too many features in natural images that are not related to the target domain. As a source domain, redundant features that are not conducive to the task will be extracted. Migration between ultrasound images can avoid this problem, but there are few types of public datasets, and it is difficult to find sufficiently similar source domains. Compared with natural images, ultrasound images have less information, and there are fewer transferable features between different ultrasound images, which may cause negative transfer. To this end, a multi-source adversarial transfer learning network for ultrasound image segmentation is proposed. Specifically, to address the lack of annotations, the idea of adversarial transfer learning is used to adaptively extract common features between a certain pair of source and target domains, which provides the possibility to utilize unlabeled ultrasound data. To alleviate the lack of knowledge in a single source domain, multi-source transfer learning is adopted to fuse knowledge from multiple source domains. In order to ensure the effectiveness of the fusion and maximize the use of precious data, a multi-source domain independent strategy is also proposed to improve the estimation of the target domain data distribution, which further increases the learning ability of the multi-source adversarial migration learning network in multiple domains.Comment: Submitted to Applied Soft Computing Journa

JIB-04 has broad-spectrum antiviral activity and inhibits SARS-CoV-2 replication and coronavirus pathogenesis

Pathogenic coronaviruses are a major threat to global public health. Here, using a recombinant reporter virus-based compound screening approach, we identified small-molecule inhibitors that potently block the replication of severe acute respiratory syndrome virus 2 (SARS-CoV-2). Among them, JIB-04 inhibited SARS-CoV-2 replication in Vero E6 cells with a 50% effective concentration of 695 nM, with a specificity index of greater than 1,000. JIB-04 showe

Market-based organizational learning in management consultancy- A case study of five small-sized management consulting companies in Norway

The ongoing technological revolution accelerates the globalization process and reduces the information differential all over the world. In the era of knowledge economy, companies must nurture a few competencies in the race to stay ahead of rivals. Organizational learning is a core capability for a company to achieve competitive advantage. Increasingly, academicians started to emphasize the importance of market information processing. This study views organizational learning from the perspective of market information processing. The ultimate goal of this research is to contribute to the creation of collective knowledge and organizational memory. Management consulting is a knowledge intensive industry, and knowledge is the power base of a consultancy. Knowledge is suggested to be one of the main forces driving the recent restructuring of the consulting industry toward an increased concentration of large, global management consulting organizations. Indeed, much scholarly attention has been devoted to organizational learning in large organizations. The extensive literature review indicates that a gap exists between the organizational learning literature and the practice of small-sized companies. This thesis intends to investigate the process on how management consultancy conducts market-based organizational learning, by examining the cases of five small-sized companies in Norway. By interviewing founders from five small-sized companies, this study reveals that small-sized companies rarely focus on building a standardized work method and knowledge management system. The empirical study indicates that small-sized companies faced a common problem, which is to enhance the organizational memory. Thus, the original market-based organizational learning framework constrains the interaction between individual tacit knowledge and collective knowledge. By means of the knowledge conversion model, this study provides a new market-based organizational learning framework for small companies. The new framework proposes that small-sized companies can rapidly leverage individual knowledge into organizational level through a redundant condition. Further, this thesis suggests the best practice of organizational learning in small-sized consulting companies