Obesity, Metabolic Syndrome, and Adipocytes

Obesity and metabolic syndromes are examples whereby excess energy consumption and energy flux disruptions are causative agents of increased fatness. Because other, as yet elucidated, cellular factors may be involved and because potential treatments of these metabolic problems involve systemic agents that are not adipose depot-specific in their actions, should we be thinking of adipose depot-specific (cellular) treatments for these problems? For sure, whether treating obesity or metabolic syndrome, the characteristics of all adipose depot-specific adipocytes and stromal vascular cells should be considered. The focus of this paper is to begin to align metabolic dysfunctions with specific characteristics of adipocytes

An empirical analysis of patents flows and R&D flows around the world

In this article, we empirically investigate the effect of Research and Development (R&D) flows on patent flows around the world. We do this using an unbalanced panel consisting primarily of Organization for Economic Co-operation and Development (OECD) countries that have both patent and R&D expenditure information broken down by domestic and foreign sources. Our analysis shows that even among a fairly homogeneous group of countries, the sources of patents and R&D differ substantially. Using a dynamic panel framework, we find that domestic R&D per capita increases domestic patents per capita only for the European Patent Convention (EPC) countries that already have a decentralized approach to innovation. Foreign R&D per capita increases foreign patents per capita in all countries even though foreign R&D constitutes a very small fraction of total R&D. We find that some of these differences can be attributed to the locations of the patent applications, including those to the European Patent Office (EPO), United States Patent and Trademark Office (USPTO) and triadic patent applications to the EPO, USPTO and Japan Patent Office (JPO) simultaneously

Scaling up prevention programmes to reduce the sexual transmission of HIV in China

Background Since 2007, sex has been the major mode of HIV transmission in China, accounting for 75% of new infections in 2009. Reducing sexual transmission is a major challenge for China in controling the HIV epidemic

Review: Animal model and the current understanding of molecule dynamics of adipogenesis

Among several potential animal models that can be used for adipogenic studies, Wagyu cattle is the one that presents unique molecular mechanisms underlying the deposit of substantial amounts of intramuscular fat. As such, this review is focused on current knowledge of such mechanisms related to adipose tissue deposition using Wagyu cattle as model. So abundant is the lipid accumulation in the skeletal muscles of these animals that in many cases, the muscle cross-sectional area appears more white (adipose tissue) than red (muscle fibers). This enhanced marbling accumulation is morphologically similar to that seen in numerous skeletal muscle dysfunctions, disease states and myopathies; this might indicate cross-similar mechanisms between such dysfunctions and fat deposition in Wagyu breed. Animal models can be used not only for a better understanding of fat deposition in livestock, but also as models to an increased comprehension on molecular mechanisms behind human conditions. This revision underlies some of the complex molecular processes of fat deposition in animals

Community evolution in patent networks: technological change and network dynamics

When studying patent data as a way to understand innovation and technological change, the conventional indicators might fall short, and categorizing technologies based on the existing classification systems used by patent authorities could cause inaccuracy and misclassification, as shown in literature. Gao et al. (International Workshop on Complex Networks and their Applications, 2017) have established a method to analyze patent classes of similar technologies as network communities. In this paper, we adopt the stabilized Louvain method for network community detection to improve consistency and stability. Incorporating the overlapping community mapping algorithm, we also develop a new method to identify the central nodes based on the temporal evolution of the network structure and track the changes of communities over time. A case study of Germany’s patent data is used to demonstrate and verify the application of the method and the results. Compared to the non-network metrics and conventional network measures, we offer a heuristic approach with a dynamic view and more stable results

Community evolution in patent networks: technological change and network dynamics

When studying patent data as a way to understand innovation and technological change, the conventional indicators might fall short, and categorizing technologies based on the existing classification systems used by patent authorities could cause inaccuracy and misclassification, as shown in literature. Gao et al. (International Workshop on Complex Networks and their Applications, 2017) have established a method to analyze patent classes of similar technologies as network communities. In this paper, we adopt the stabilized Louvain method for network community detection to improve consistency and stability. Incorporating the overlapping community mapping algorithm, we also develop a new method to identify the central nodes based on the temporal evolution of the network structure and track the changes of communities over time. A case study of Germany’s patent data is used to demonstrate and verify the application of the method and the results. Compared to the non-network metrics and conventional network measures, we offer a heuristic approach with a dynamic view and more stable results

Do Employment Quotas Explain the Occupational Choices of Disadvantaged Minorities in India?

This article investigates the effects of a large-scale public sector employment quota policy for disadvantaged minorities (Scheduled Castes and Scheduled Tribes) in India on their occupational choices, as defined by skill level, during the 1980s and 1990s. We find that, first, the employment quota policy significantly affects the occupational structure of both disadvantaged minority populations. In response to the employment quotas, individuals belonging to the Scheduled Caste group are more likely to choose high-skill occupations and less likely to choose low- and middle-skill occupations, while individuals belonging to the Scheduled Tribe group are less likely to choose high-skill occupations and more likely to choose low- and middle-skill occupations. Second, the impact of the employment quotas is significantly related with an individual's years of schooling. Overall, the results indicate that the employment quota policy changes the occupational choices of individuals within the targeted populations and contributes to their improved socio-economic standing

On the Polynomial Measurement Error Model

This paper discusses point estimation of the coefficients of polynomial measurement error (errors-in-variables) models. This includes functional and structural models. The connection between these models and total least squares (TLS) is also examined. A compendium of existing as well as new results is presented

Endogeneity in Panel Data Models with Time-Varying and Time-Fixed Regressors: To IV or Not IV?

We analyse the problem of parameter inconsistency in panel data econometrics due to the correlation of exogenous variables with the error term. A common solution in this setting is to use Instrumental-Variable (IV) estimation in the spirit of Hausman-Taylor (1981). However, some potential shortcomings of the latter approach recently gave rise to the use of non-IV two-step estimators. Given their growing number of empirical applications, we aim to systematically compare the performance of IV and non-IV approaches in the presence of time-fixed variables and right hand side endogeneity using Monte Carlo simulations, where we explicitly control for the problem of IV selection in the Hausman-Taylor case. The simulation results show that the Hausman- Taylor model with perfect-knowledge about the underlying data structure (instrument orthogonality) has on average the smallest bias. However, compared to the empirically relevant specification with imperfect-knowledge and instruments chosen by statistical criteria, the non-IV rival performs equally well or even better especially in terms of estimating variable coefficients for time- fixed regressors. Moreover, the non-IV method tends to have a smaller root mean square error (rmse) than both Hausman-Taylor models with perfect and imperfect knowledge about the underlying correlation between r.h.s variables and residual term. This indicates that it is generally more efficient. The results are roughly robust for various combinations in the time and cross-section dimension of the data